Business competition between manufacturing businesses in Indonesia is getting
tighter along with the development of businesses from competing companies that have
similar businesses. One strategy that can be applied by this company is Business
Intelligence, that is by utilizing the data that is already available to help in better
decision making, such as decisions based on facts stored in the data, precisely namely
the lack of errors in the presentation of reports, and fast that is, cut down on the time
for making the usual report. The method proposed by the author is a method that can
be used to predict sales value based on existing sales data (sales forecasting). By
implementing Business Intelligence and data mining, companies can learn from the
data that has been collected, can evaluate the performance of the sales department,
can understand market trends from the products sold, and can predict future sales
levels. In addition, Business Intelligence can display detailed transaction data
recapitulation quickly.
A STUDY ON PERCEPTION OF INTERNET BANKING USERS SERVICE QUALITY - A STRUCTURA...IAEME Publication
The purpose of the study is to identify the perceptions of Internet banking (IB) users in Tamil Nadu using technology acceptance model (TAM) by incorporating service quality as external variable. The study found that both the TAM variables – perceived ease of use (PEOU) and perceived usefulness (PU). A total of 380 questionnaires were distributed for internet banking customers and 336 were returned (resulting 88.42 percentage of response rate). The results confirm that the all six dimensions (Website attribute, Reliability, Responsiveness, Fulfillment, Efficiency and Privacy) are distinct constructs. The results also indicate that internet banking service quality consisting of six dimensions has appropriate reliability and each dimension has a significant relationship with internet banking service quality. The efficiency of banking website is the important aspect of internet banking service quality. The finding found that the relationship between internet banking service quality, perceived ease of use and perceived usefulness are significant. This study proposes a model to understand the effect of internet banking service quality on perceived ease of use and perceived usefulness in developing country. The constructs truly reflect the dynamism of customers’ banking relationship and a better understanding the attitude on internet banking will help the bankers in implementing more effective marketing strategies.
Thriving information system through business intelligence knowledge managemen...IJECEIAES
In the current digitalization dilemma of an organization, there is a need for the business intelligence and knowledge management element for enhancing a perspective of learning and strategic management. These elements will comprise a significant evolution of learning, insight gained, experiences and knowledge through compelling theoretical impact for practitioners, academicians, and scholars in the pertinent field of interest. This phenomenon occurs due to digitalization transformation towards industry revolution 5.0 and organizational excellence in the information system area. This research focuses on the characteristic of a comprehensive performance measure perspective in an organization that conceives information assessment and key challenges of Business Intelligence and Knowledge Management in perceiving a relevant organizational excellence framework. The dynamic research focusing on the decision-making process and leveraging better knowledge creation. The future of organization excellence seemed to be convergent in determining the holistic performance measure perspective and its factors towards industry revolution 5.0. The research ends up with a typical basic excellence framework that will mash up some characteristics in designing an organizational strategic performance framework. The output is a conceptual performance measure framework for a typical decision-making application for organizational strategic performance management dashboarding.
The analytics industry is growing for sure and Analytics India Magazine in association with AnalytixLabs brings the Analytics India Industry study 2017 covering all the aspects of the analytics industry. The study is a result of extensive primary and secondary research conducted over a duration of two months.
State of data_science_in_domestic_indian_market_2019_aim_sasSrishti Deoras
This document provides an overview of analytics and data science adoption in large Indian companies based on a study conducted in 2019. Some key findings:
- Analytics adoption has increased to 70% of large firms from 64% last year. Sectors like banking, auto and e-commerce have nearly 100% adoption.
- Mumbai accounts for 44% of analytics functions, followed by Delhi and Bangalore which together account for 91% of functions.
- On average, analytics penetration is 2.5% of employees and tenure is 4 years, up from 2.8% and 3.4 years respectively last year.
- Telecom professionals have the highest experience at 10.2 years while e-commerce has the lowest tenure at
In the latest edition of the Indian analytics study, AIM Research, in association with AnalytixLabs, provides insights on the overall analytics domain and the state of analytics across sectors and enterprises.
Adopting Customer Centric Approach towards Customer Relationship Management i...ijtsrd
As the Indian economy focuses on future growth models, its railway system has been an integral part of this, undergoing a phased transformation since January 2018. The railways are set to progress towards a modern, efficient, and digitized network with a focus on improving insights, efficiencies, and capabilities. By 2030, the Indian government plans to spend US 70 billion to upgrade its railway network into an electric and digitized platform. It is also opening the state owned conglomerate to private companies for operating passenger trains, manufacturing coaches and locomotives, and redeveloping railway stations. While funds have been allocated to revamp various railways projects, the Indian Railways continues to face three big challenges under investment for the creation of infrastructure, people management, and the need for technology upgrade. Pradeep Kumar "Adopting Customer Centric Approach towards Customer Relationship Management in Reference to North-Eastern Railways" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, URL: https://www.ijtsrd.compapers/ijtsrd43740.pdf Paper URL: https://www.ijtsrd.commanagement/consumer-behaviour/43740/adopting-customer-centric-approach-towards-customer-relationship-management-in-reference-to-northeastern-railways/pradeep-kumar
Banking Sector plays a key role in investment, growth, and in the development of different industries around the world. Because accounting information systems (AIS) play a key role in determining the degree of success, and affect the competitive position of commercial banks in a world that characterized with globalization, these systems need more investigation.
In the latest edition of the Indian analytics study, AIM Research, in association with AnalytixLabs, provides insights on the overall analytics domain and the state of analytics across sectors and enterprises.
A STUDY ON PERCEPTION OF INTERNET BANKING USERS SERVICE QUALITY - A STRUCTURA...IAEME Publication
The purpose of the study is to identify the perceptions of Internet banking (IB) users in Tamil Nadu using technology acceptance model (TAM) by incorporating service quality as external variable. The study found that both the TAM variables – perceived ease of use (PEOU) and perceived usefulness (PU). A total of 380 questionnaires were distributed for internet banking customers and 336 were returned (resulting 88.42 percentage of response rate). The results confirm that the all six dimensions (Website attribute, Reliability, Responsiveness, Fulfillment, Efficiency and Privacy) are distinct constructs. The results also indicate that internet banking service quality consisting of six dimensions has appropriate reliability and each dimension has a significant relationship with internet banking service quality. The efficiency of banking website is the important aspect of internet banking service quality. The finding found that the relationship between internet banking service quality, perceived ease of use and perceived usefulness are significant. This study proposes a model to understand the effect of internet banking service quality on perceived ease of use and perceived usefulness in developing country. The constructs truly reflect the dynamism of customers’ banking relationship and a better understanding the attitude on internet banking will help the bankers in implementing more effective marketing strategies.
Thriving information system through business intelligence knowledge managemen...IJECEIAES
In the current digitalization dilemma of an organization, there is a need for the business intelligence and knowledge management element for enhancing a perspective of learning and strategic management. These elements will comprise a significant evolution of learning, insight gained, experiences and knowledge through compelling theoretical impact for practitioners, academicians, and scholars in the pertinent field of interest. This phenomenon occurs due to digitalization transformation towards industry revolution 5.0 and organizational excellence in the information system area. This research focuses on the characteristic of a comprehensive performance measure perspective in an organization that conceives information assessment and key challenges of Business Intelligence and Knowledge Management in perceiving a relevant organizational excellence framework. The dynamic research focusing on the decision-making process and leveraging better knowledge creation. The future of organization excellence seemed to be convergent in determining the holistic performance measure perspective and its factors towards industry revolution 5.0. The research ends up with a typical basic excellence framework that will mash up some characteristics in designing an organizational strategic performance framework. The output is a conceptual performance measure framework for a typical decision-making application for organizational strategic performance management dashboarding.
The analytics industry is growing for sure and Analytics India Magazine in association with AnalytixLabs brings the Analytics India Industry study 2017 covering all the aspects of the analytics industry. The study is a result of extensive primary and secondary research conducted over a duration of two months.
State of data_science_in_domestic_indian_market_2019_aim_sasSrishti Deoras
This document provides an overview of analytics and data science adoption in large Indian companies based on a study conducted in 2019. Some key findings:
- Analytics adoption has increased to 70% of large firms from 64% last year. Sectors like banking, auto and e-commerce have nearly 100% adoption.
- Mumbai accounts for 44% of analytics functions, followed by Delhi and Bangalore which together account for 91% of functions.
- On average, analytics penetration is 2.5% of employees and tenure is 4 years, up from 2.8% and 3.4 years respectively last year.
- Telecom professionals have the highest experience at 10.2 years while e-commerce has the lowest tenure at
In the latest edition of the Indian analytics study, AIM Research, in association with AnalytixLabs, provides insights on the overall analytics domain and the state of analytics across sectors and enterprises.
Adopting Customer Centric Approach towards Customer Relationship Management i...ijtsrd
As the Indian economy focuses on future growth models, its railway system has been an integral part of this, undergoing a phased transformation since January 2018. The railways are set to progress towards a modern, efficient, and digitized network with a focus on improving insights, efficiencies, and capabilities. By 2030, the Indian government plans to spend US 70 billion to upgrade its railway network into an electric and digitized platform. It is also opening the state owned conglomerate to private companies for operating passenger trains, manufacturing coaches and locomotives, and redeveloping railway stations. While funds have been allocated to revamp various railways projects, the Indian Railways continues to face three big challenges under investment for the creation of infrastructure, people management, and the need for technology upgrade. Pradeep Kumar "Adopting Customer Centric Approach towards Customer Relationship Management in Reference to North-Eastern Railways" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-4 , June 2021, URL: https://www.ijtsrd.compapers/ijtsrd43740.pdf Paper URL: https://www.ijtsrd.commanagement/consumer-behaviour/43740/adopting-customer-centric-approach-towards-customer-relationship-management-in-reference-to-northeastern-railways/pradeep-kumar
Banking Sector plays a key role in investment, growth, and in the development of different industries around the world. Because accounting information systems (AIS) play a key role in determining the degree of success, and affect the competitive position of commercial banks in a world that characterized with globalization, these systems need more investigation.
In the latest edition of the Indian analytics study, AIM Research, in association with AnalytixLabs, provides insights on the overall analytics domain and the state of analytics across sectors and enterprises.
Case Study, Cairo-Amman Bank-Jordan: Improving an Organization by the use of ...journal ijrtem
Abstract : In this study, analysis and comparison between the most important enterprise systems Enterprise Resource Planning (ERP), Supply Chain Management (SCM), and Customer Relationship Management (CRM) are studied in accordance with the organization innovation performance as a special case Cairo Amman Bank in Jordan for process and as well the CRM while using smart phones and iPads as product innovations. Moreover, this study employed a database obtained from two computers aided, mobile surveys conducted since 2010 by the Cairo Amman Bank in Jordan. Both studies are focused along the dispersal and use of the information and communication technology (ICT) in Cairo Amman Bank and its ramifications. Each database contained information about 4000 customers with more than five employees, these databases representatively choose from the most important services in the bank. These databases are taken for the sample which is furnished from the credit rating employees or agents. This agency who provides the biggest database on organizations available in Jordan. Moreover, collects basic information about customers as addresses, sectors, organization’s sizes in the market, and sizes in all enterprises that applied to the bank for credits. These excerpts from the populations of Jordan organizations were stratified according to two size categories, as Jordan and Palestine (East/West) and to several branches in both states. As many organizations as needed have been asked until all classes were met. The interviewee was, in general, the principal executive officer of the organizations who could also resolve to legislate on queries to a corresponding employee like, e. g.,
IRJET- E-Commerce Recommender System using Data Mining AlgorithmsIRJET Journal
This document summarizes a research paper that proposes improvements to recommender systems for e-commerce businesses. It addresses issues like limited product availability, new customers with no purchase history, and timeliness of data. The authors propose a hybrid algorithm using collaborative filtering to recommend limited products, and a random algorithm to recommend products to new customers based on other customers with similar interests. The system was developed using ASP.NET, C#, and SQL Server. Experimental results showed the approaches helped address cold start situations and provide personalized recommendations. The authors conclude the techniques can improve e-commerce business efficiency and effectiveness.
Application of Big Data in Enterprise Managementijtsrd
The document discusses the application of big data in enterprise management. It begins by outlining three key characteristics of big data: huge data capacity, fast data processing speed, and data diversity. It then explains the importance of big data for enterprises, such as activating the value of massive data, getting user feedback quickly, and providing product correlation analysis. Some main challenges of enterprise management in a big data environment are also covered, such as backward ideas and a lack of innovation. Finally, the document discusses several ways big data can be applied in enterprises, including innovating management concepts, transforming marketing strategies, improving management platforms, market forecasting, developing resources, and reducing costs.
Analytics & Data Science Industry In India: Study 2018 - by AnalytixLabs & AIMAnalytics India Magazine
The data analytics market in India is growing at a fast pace, with companies and startups offering analytics services and products catering to various industries. Different sectors have seen different penetration and adoption of analytics, and so is the revenue generation from these sectors.
The Analytics and Data Science Industry Study 2018 takes into account various trends that analytics industry in India is witnessing, revenue generated through various geographies, analytics market size by sector, across cities etc. It also takes into consideration analytics professionals in India across work experience and education.
This year’s study is brought to you in association with AnalytixLabs, a pioneer and one of the first analytics training institutes in India. The study is a result of extensive primary and secondary research conducted over a duration of two months, where we got in touch with analytics companies and professionals across various industries such as banking, finance, ecommerce, retail, pharma, healthcare and others.
The document discusses business intelligence and analytics in India, including trends, challenges, and growth. It notes that while the industry in India is growing, it faces challenges like a lack of relevant data, shortage of skilled workers, fragmented market, and need for more domain-specific education. However, trends like a growing focus on industries like retail and banking, and increased use of mobile business intelligence, are supporting the growth of the industry. The industry is expected to reach revenues of $140 million in India by 2014.
Sit717 enterprise business intelligence 2019 t2 copy1NellutlaKishore
This document discusses data mining techniques and business intelligence. It begins with an introduction to different data mining techniques like clustering, statistical analysis, visualization, classification, neural networks, rules, and decision trees. It then provides more detail on statistical techniques, explaining that they help analyze large datasets. The document evaluates how big data and business intelligence are related, concluding that while they are different concepts, they need to work together to effectively analyze data and make smart business decisions. Big data provides the large datasets, while business intelligence extracts useful information from those datasets.
Background: As a result of enormous progress in the information technology and communications, several
organizations adopt business intelligence (BI) applications in order to cope with the development in
business mechanisms, staying at the marketplace, competition, customer possession and retention.
The rapid growing capabilities of both generating and gathering data has created an imperative
necessity for new techniques and tools can intelligently and automatically transform the processed data in
to a valuable information and knowledge. Knowledge management is a cornerstone in selecting accurate
information at the appropriate time from many relevant resources.
Objective: The major Objective of this research is to "examine the impact of business intelligence on
employee's knowledge sharing at the Jordanian telecommunications company (JTC)".
Design/methodology/approach: A review of the literature serves as the basis for measuring the impact of
business intelligence using knowledge sharing scale. The study sample consisted of administrators,
technical staff, and senior managers.75 questionnaires were distributed in the site of JTC. (70)
Questionnaires were collected. (63) Found statistically usable for this study representing a response rate
of (84 %).
Findings: Most important findings for this study demonstrate that business intelligence tools respectively
(OLAP, Data Warehousing, and Data Mining)are highly effect on employee knowledge sharing.
Originality/ Value: Business Intelligence play a significant role in obtaining the underlying knowledge in
the organization, through optimum utilization of data sources the internal and external alike. Several
researches addressed the importance of integrating business intelligence with knowledge management,
little of these researches addressing the impact of business intelligence on knowledge sharing. This study
has tried to address this need.
Data science ai_trends_india_2020_analytics_india_magazineSrishti Deoras
The document discusses key data science and AI trends to watch out for in India in 2020 according to a report by Analytics India Magazine and AnalytixLabs. Some of the major trends highlighted include the rise of hyper automation, development of more humanized AI products, advancements in natural language processing and conversational AI, increased focus on explainable AI, growth of augmented analytics, innovations in data storage technologies, greater emphasis on data privacy, raising awareness on ethical use of AI, and potential opportunities around quantum computing and data science. The report examines each of these trends in further detail to outline what companies and industries can expect to see changing or developing in the upcoming year.
Impact on Jobs across Emerging Technologies During the Current Pandemic Crisi...Srishti Deoras
Analytics India Magazine (AIM) along with Jigsaw Academy, has developed this study to focus on the impact on jobs across certain emerging technologies.
Analytics & Data Science Industry in India: Study 2019 by AIM & Praxis Busine...Richa Bhatia
Our annual Analytics & Data Science Industry In India: Study 2019 by Analytics India Magazine and Praxis Business School identifies the key trends and revenue drivers for the analytics industry. We take stock of the burgeoning analytics industry in India — domestic and outsourcing, the leading revenue generators, the geographies served and where the analytics market is heading.
Value creation with big data analytics for enterprises: a surveyTELKOMNIKA JOURNAL
The emergence of Big Data applications has paved the way for enterprises to use Big Data as a value-creation strategy for their business; however, the majority of enterprises fail to know how to generate value from their massive volumes of data. Big Data Analytics results can help the enterprises in better decision-making and provide them with additional profits. Studying different researches dedicated to value creation through Big Data Analytics. This paper (a) highlights the current state of the art proposed for creating value from Big Data Analytics, (b) identifies the essential factors and discusses their effects upon value creation, and (c) provides a classification of the cutting-edge technologies in this field.
This document discusses using Microsoft Excel 2013 and Microsoft Access to create an offers bank decision support system (DSS). It proposes a 4 phase approach: 1) Create a database and star schema using Access, 2) Fill the database with data by defining dimensions and measures and retrieving data in Excel, 3) Create a dashboard in Excel, 4) Analyze past trends and predict future trends using data mining. The document also provides background on business intelligence solutions and reviews literature on using BI to turn raw data into meaningful business insights.
Financial development and economic growth in nigeriaAlexander Decker
The document discusses the relationship between financial development and economic growth in Nigeria. It analyzes previous literature on the topic which shows mixed findings on the direction of the relationship. The study aims to contribute new evidence on how financial development impacts economic growth in Nigeria using time series data and econometric modeling. Preliminary results suggest a long-run relationship between financial development indicators like bank credit and economic growth as measured by GDP. However, some variables like lending rates did not have the expected effect. The paper concludes with recommendations for policies to strengthen this relationship and foster growth.
Business intelligence environments involve collecting data from various sources, transforming and organizing it using tools like ETL, and storing it in data warehouses or marts. This data is then analyzed using OLAP and reporting tools to provide useful information for business decisions. Setting up an effective BI environment requires understanding business requirements, defining processes, determining data needs, integrating data sources, and selecting appropriate tools and techniques. Careful planning and skilled people are needed to ensure the BI environment supports organizational goals.
State of analytics in domestic firms in India 2017 - by AIM & Cartesian Consu...Analytics India Magazine
Analytics industry in gaining importance in India and is being deployed across various sectors such as banking, finance, e-commerce, retail, and telecom. Tapping on to the growing analytics industry, the study gives us a quick insight into how the analytics scenario is evolving in the domestic market.
This year’s study has been co-presented by Cartesian Consulting, a global analytics services firm specialising in customer, marketing, and business analytics. We looked at 20 large Indian firms across industries that have adopted analytics to improve business.
Drivers of e business value creation inIJMIT JOURNAL
With the development and growth of internet, its applications of e-banking, e-commerce, and e-business
became irreplaceable channels regarding its fast access, rich content, and smooth interactivity. High
investments are paid toward improving the quality of service offered by the banks. This paper is dedicated
to empirically investigating the drivers of e-Business value creation in the Jordanian banking sector. This
work summarizes the main differences among employees of Jordanian and foreign bank regarding their
perspectives. Many of the competing foreign banks to the Jordanian banks are enforced with huge financial
capital, having long periods of banking practices and are employing cutting-edge technologies and tools.
To minimize the technological gap, Jordanian banks are working hard to develop their e-Business services.
This in one hand has to enhance their trust, satisfaction, and commitment toward existing customers and
entice new comers on other hand. Based on business model of Amit and Zott, i.e. the four constructs of e-
Value framework (efficiency, complementarities, lock-in, and novelty), four hypotheses have been
formulated to test the differences in the drivers of e-Business value creation between Jordanian and foreign
banks. A survey questionnaire in a form of paper-and-pencil was delivered personally to 200 employees
from four main Jordanian banks and 200 employees from four foreign banks working in Jordan. The
questionnaire was formed and constructed to test the proposed hypotheses. the findings in this study based
on the SEM and T-test analyses, revealed important implications that will help banks’ managers to make
well-informed decisions and policies regarding investments and resources allocation for implementing e-
Business strategies and ventures. The paper concludes with discussing the importance of these findings for
practitioners and for future research on value accrued from e-Business services.
Asl rof businessintelligencetechnology2019kamilHussain15
This document presents a systematic literature review on business intelligence technology, contributions, and applications for higher education. The methodology used PRISMA to identify relevant research. 12 articles were included from databases based on screening criteria. To answer the research questions, the included articles were analyzed. For technology (Q1), business intelligence techniques identified were data mining, viable system model, learning analytics, cloud computing, and behavioral analytics. Tools included Hadoop, Gephi, BigData by IBM, and web-based. Contributions (Q2) were knowledge transfer, innovation, and evaluation. Applications (Q3) included research, curriculum, assessment, behavior analysis, student enrollment, and resource management.
Business intelligence (BI) involves strategies and technologies used to analyze business data and present information to support decision-making. Big data refers to extremely large datasets that require advanced analytics to derive insights. BI technologies provide historical, current, and predictive views of business operations through reporting, analytics, and data mining. While BI helps with reporting, budgeting, forecasting, and promotions, it can be costly and expose information to risks. Big data allows for detecting fraud, gaining competitive insights, and improving customer service and profits through real-time analysis, but poses logistical and privacy challenges.
This document summarizes a systematic literature review of 62 articles on business intelligence and analytics (BI&A) in small and medium enterprises (SMEs). The review identified several research topics addressed in the literature, including BI&A components, solutions, mobile and cloud BI&A, applications, adoption, implementation, and benefits. However, the review also found few studies focused specifically on BI&A in SMEs. The review synthesized the literature to understand the current state of research and identify gaps to inform future work on advancing BI&A in SMEs.
Data Mining Based Store Layout Architecture for SupermarketIRJET Journal
This document discusses using data mining techniques to develop an efficient store layout for supermarkets. It proposes using association rule mining on transaction data to uncover frequent itemsets purchased together by customers. This can help determine what products to place near each other to increase sales. The document first provides background on data mining and how it can help with decision support. It then describes how association rule mining and the Apriori algorithm can be applied to market basket analysis to analyze customer purchasing patterns and generate rules on related products. The goal is to develop a more customer-oriented store layout based on these rules rather than traditional category-based layouts.
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This document provides an overview of business intelligence (BI), including what it is, how it is implemented, examples of how organizations use BI, and the typical components involved in a BI architecture. It defines BI as a set of processes and technologies that convert raw data into meaningful and useful information for driving business decisions. The key components of a BI architecture discussed are data sources, data integration and cleansing tools, analytics data stores, BI and visualization tools, and dashboards/reports for delivering insights.
Case Study, Cairo-Amman Bank-Jordan: Improving an Organization by the use of ...journal ijrtem
Abstract : In this study, analysis and comparison between the most important enterprise systems Enterprise Resource Planning (ERP), Supply Chain Management (SCM), and Customer Relationship Management (CRM) are studied in accordance with the organization innovation performance as a special case Cairo Amman Bank in Jordan for process and as well the CRM while using smart phones and iPads as product innovations. Moreover, this study employed a database obtained from two computers aided, mobile surveys conducted since 2010 by the Cairo Amman Bank in Jordan. Both studies are focused along the dispersal and use of the information and communication technology (ICT) in Cairo Amman Bank and its ramifications. Each database contained information about 4000 customers with more than five employees, these databases representatively choose from the most important services in the bank. These databases are taken for the sample which is furnished from the credit rating employees or agents. This agency who provides the biggest database on organizations available in Jordan. Moreover, collects basic information about customers as addresses, sectors, organization’s sizes in the market, and sizes in all enterprises that applied to the bank for credits. These excerpts from the populations of Jordan organizations were stratified according to two size categories, as Jordan and Palestine (East/West) and to several branches in both states. As many organizations as needed have been asked until all classes were met. The interviewee was, in general, the principal executive officer of the organizations who could also resolve to legislate on queries to a corresponding employee like, e. g.,
IRJET- E-Commerce Recommender System using Data Mining AlgorithmsIRJET Journal
This document summarizes a research paper that proposes improvements to recommender systems for e-commerce businesses. It addresses issues like limited product availability, new customers with no purchase history, and timeliness of data. The authors propose a hybrid algorithm using collaborative filtering to recommend limited products, and a random algorithm to recommend products to new customers based on other customers with similar interests. The system was developed using ASP.NET, C#, and SQL Server. Experimental results showed the approaches helped address cold start situations and provide personalized recommendations. The authors conclude the techniques can improve e-commerce business efficiency and effectiveness.
Application of Big Data in Enterprise Managementijtsrd
The document discusses the application of big data in enterprise management. It begins by outlining three key characteristics of big data: huge data capacity, fast data processing speed, and data diversity. It then explains the importance of big data for enterprises, such as activating the value of massive data, getting user feedback quickly, and providing product correlation analysis. Some main challenges of enterprise management in a big data environment are also covered, such as backward ideas and a lack of innovation. Finally, the document discusses several ways big data can be applied in enterprises, including innovating management concepts, transforming marketing strategies, improving management platforms, market forecasting, developing resources, and reducing costs.
Analytics & Data Science Industry In India: Study 2018 - by AnalytixLabs & AIMAnalytics India Magazine
The data analytics market in India is growing at a fast pace, with companies and startups offering analytics services and products catering to various industries. Different sectors have seen different penetration and adoption of analytics, and so is the revenue generation from these sectors.
The Analytics and Data Science Industry Study 2018 takes into account various trends that analytics industry in India is witnessing, revenue generated through various geographies, analytics market size by sector, across cities etc. It also takes into consideration analytics professionals in India across work experience and education.
This year’s study is brought to you in association with AnalytixLabs, a pioneer and one of the first analytics training institutes in India. The study is a result of extensive primary and secondary research conducted over a duration of two months, where we got in touch with analytics companies and professionals across various industries such as banking, finance, ecommerce, retail, pharma, healthcare and others.
The document discusses business intelligence and analytics in India, including trends, challenges, and growth. It notes that while the industry in India is growing, it faces challenges like a lack of relevant data, shortage of skilled workers, fragmented market, and need for more domain-specific education. However, trends like a growing focus on industries like retail and banking, and increased use of mobile business intelligence, are supporting the growth of the industry. The industry is expected to reach revenues of $140 million in India by 2014.
Sit717 enterprise business intelligence 2019 t2 copy1NellutlaKishore
This document discusses data mining techniques and business intelligence. It begins with an introduction to different data mining techniques like clustering, statistical analysis, visualization, classification, neural networks, rules, and decision trees. It then provides more detail on statistical techniques, explaining that they help analyze large datasets. The document evaluates how big data and business intelligence are related, concluding that while they are different concepts, they need to work together to effectively analyze data and make smart business decisions. Big data provides the large datasets, while business intelligence extracts useful information from those datasets.
Background: As a result of enormous progress in the information technology and communications, several
organizations adopt business intelligence (BI) applications in order to cope with the development in
business mechanisms, staying at the marketplace, competition, customer possession and retention.
The rapid growing capabilities of both generating and gathering data has created an imperative
necessity for new techniques and tools can intelligently and automatically transform the processed data in
to a valuable information and knowledge. Knowledge management is a cornerstone in selecting accurate
information at the appropriate time from many relevant resources.
Objective: The major Objective of this research is to "examine the impact of business intelligence on
employee's knowledge sharing at the Jordanian telecommunications company (JTC)".
Design/methodology/approach: A review of the literature serves as the basis for measuring the impact of
business intelligence using knowledge sharing scale. The study sample consisted of administrators,
technical staff, and senior managers.75 questionnaires were distributed in the site of JTC. (70)
Questionnaires were collected. (63) Found statistically usable for this study representing a response rate
of (84 %).
Findings: Most important findings for this study demonstrate that business intelligence tools respectively
(OLAP, Data Warehousing, and Data Mining)are highly effect on employee knowledge sharing.
Originality/ Value: Business Intelligence play a significant role in obtaining the underlying knowledge in
the organization, through optimum utilization of data sources the internal and external alike. Several
researches addressed the importance of integrating business intelligence with knowledge management,
little of these researches addressing the impact of business intelligence on knowledge sharing. This study
has tried to address this need.
Data science ai_trends_india_2020_analytics_india_magazineSrishti Deoras
The document discusses key data science and AI trends to watch out for in India in 2020 according to a report by Analytics India Magazine and AnalytixLabs. Some of the major trends highlighted include the rise of hyper automation, development of more humanized AI products, advancements in natural language processing and conversational AI, increased focus on explainable AI, growth of augmented analytics, innovations in data storage technologies, greater emphasis on data privacy, raising awareness on ethical use of AI, and potential opportunities around quantum computing and data science. The report examines each of these trends in further detail to outline what companies and industries can expect to see changing or developing in the upcoming year.
Impact on Jobs across Emerging Technologies During the Current Pandemic Crisi...Srishti Deoras
Analytics India Magazine (AIM) along with Jigsaw Academy, has developed this study to focus on the impact on jobs across certain emerging technologies.
Analytics & Data Science Industry in India: Study 2019 by AIM & Praxis Busine...Richa Bhatia
Our annual Analytics & Data Science Industry In India: Study 2019 by Analytics India Magazine and Praxis Business School identifies the key trends and revenue drivers for the analytics industry. We take stock of the burgeoning analytics industry in India — domestic and outsourcing, the leading revenue generators, the geographies served and where the analytics market is heading.
Value creation with big data analytics for enterprises: a surveyTELKOMNIKA JOURNAL
The emergence of Big Data applications has paved the way for enterprises to use Big Data as a value-creation strategy for their business; however, the majority of enterprises fail to know how to generate value from their massive volumes of data. Big Data Analytics results can help the enterprises in better decision-making and provide them with additional profits. Studying different researches dedicated to value creation through Big Data Analytics. This paper (a) highlights the current state of the art proposed for creating value from Big Data Analytics, (b) identifies the essential factors and discusses their effects upon value creation, and (c) provides a classification of the cutting-edge technologies in this field.
This document discusses using Microsoft Excel 2013 and Microsoft Access to create an offers bank decision support system (DSS). It proposes a 4 phase approach: 1) Create a database and star schema using Access, 2) Fill the database with data by defining dimensions and measures and retrieving data in Excel, 3) Create a dashboard in Excel, 4) Analyze past trends and predict future trends using data mining. The document also provides background on business intelligence solutions and reviews literature on using BI to turn raw data into meaningful business insights.
Financial development and economic growth in nigeriaAlexander Decker
The document discusses the relationship between financial development and economic growth in Nigeria. It analyzes previous literature on the topic which shows mixed findings on the direction of the relationship. The study aims to contribute new evidence on how financial development impacts economic growth in Nigeria using time series data and econometric modeling. Preliminary results suggest a long-run relationship between financial development indicators like bank credit and economic growth as measured by GDP. However, some variables like lending rates did not have the expected effect. The paper concludes with recommendations for policies to strengthen this relationship and foster growth.
Business intelligence environments involve collecting data from various sources, transforming and organizing it using tools like ETL, and storing it in data warehouses or marts. This data is then analyzed using OLAP and reporting tools to provide useful information for business decisions. Setting up an effective BI environment requires understanding business requirements, defining processes, determining data needs, integrating data sources, and selecting appropriate tools and techniques. Careful planning and skilled people are needed to ensure the BI environment supports organizational goals.
State of analytics in domestic firms in India 2017 - by AIM & Cartesian Consu...Analytics India Magazine
Analytics industry in gaining importance in India and is being deployed across various sectors such as banking, finance, e-commerce, retail, and telecom. Tapping on to the growing analytics industry, the study gives us a quick insight into how the analytics scenario is evolving in the domestic market.
This year’s study has been co-presented by Cartesian Consulting, a global analytics services firm specialising in customer, marketing, and business analytics. We looked at 20 large Indian firms across industries that have adopted analytics to improve business.
Drivers of e business value creation inIJMIT JOURNAL
With the development and growth of internet, its applications of e-banking, e-commerce, and e-business
became irreplaceable channels regarding its fast access, rich content, and smooth interactivity. High
investments are paid toward improving the quality of service offered by the banks. This paper is dedicated
to empirically investigating the drivers of e-Business value creation in the Jordanian banking sector. This
work summarizes the main differences among employees of Jordanian and foreign bank regarding their
perspectives. Many of the competing foreign banks to the Jordanian banks are enforced with huge financial
capital, having long periods of banking practices and are employing cutting-edge technologies and tools.
To minimize the technological gap, Jordanian banks are working hard to develop their e-Business services.
This in one hand has to enhance their trust, satisfaction, and commitment toward existing customers and
entice new comers on other hand. Based on business model of Amit and Zott, i.e. the four constructs of e-
Value framework (efficiency, complementarities, lock-in, and novelty), four hypotheses have been
formulated to test the differences in the drivers of e-Business value creation between Jordanian and foreign
banks. A survey questionnaire in a form of paper-and-pencil was delivered personally to 200 employees
from four main Jordanian banks and 200 employees from four foreign banks working in Jordan. The
questionnaire was formed and constructed to test the proposed hypotheses. the findings in this study based
on the SEM and T-test analyses, revealed important implications that will help banks’ managers to make
well-informed decisions and policies regarding investments and resources allocation for implementing e-
Business strategies and ventures. The paper concludes with discussing the importance of these findings for
practitioners and for future research on value accrued from e-Business services.
Asl rof businessintelligencetechnology2019kamilHussain15
This document presents a systematic literature review on business intelligence technology, contributions, and applications for higher education. The methodology used PRISMA to identify relevant research. 12 articles were included from databases based on screening criteria. To answer the research questions, the included articles were analyzed. For technology (Q1), business intelligence techniques identified were data mining, viable system model, learning analytics, cloud computing, and behavioral analytics. Tools included Hadoop, Gephi, BigData by IBM, and web-based. Contributions (Q2) were knowledge transfer, innovation, and evaluation. Applications (Q3) included research, curriculum, assessment, behavior analysis, student enrollment, and resource management.
Business intelligence (BI) involves strategies and technologies used to analyze business data and present information to support decision-making. Big data refers to extremely large datasets that require advanced analytics to derive insights. BI technologies provide historical, current, and predictive views of business operations through reporting, analytics, and data mining. While BI helps with reporting, budgeting, forecasting, and promotions, it can be costly and expose information to risks. Big data allows for detecting fraud, gaining competitive insights, and improving customer service and profits through real-time analysis, but poses logistical and privacy challenges.
This document summarizes a systematic literature review of 62 articles on business intelligence and analytics (BI&A) in small and medium enterprises (SMEs). The review identified several research topics addressed in the literature, including BI&A components, solutions, mobile and cloud BI&A, applications, adoption, implementation, and benefits. However, the review also found few studies focused specifically on BI&A in SMEs. The review synthesized the literature to understand the current state of research and identify gaps to inform future work on advancing BI&A in SMEs.
Data Mining Based Store Layout Architecture for SupermarketIRJET Journal
This document discusses using data mining techniques to develop an efficient store layout for supermarkets. It proposes using association rule mining on transaction data to uncover frequent itemsets purchased together by customers. This can help determine what products to place near each other to increase sales. The document first provides background on data mining and how it can help with decision support. It then describes how association rule mining and the Apriori algorithm can be applied to market basket analysis to analyze customer purchasing patterns and generate rules on related products. The goal is to develop a more customer-oriented store layout based on these rules rather than traditional category-based layouts.
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This document provides an overview of business intelligence (BI), including what it is, how it is implemented, examples of how organizations use BI, and the typical components involved in a BI architecture. It defines BI as a set of processes and technologies that convert raw data into meaningful and useful information for driving business decisions. The key components of a BI architecture discussed are data sources, data integration and cleansing tools, analytics data stores, BI and visualization tools, and dashboards/reports for delivering insights.
This document summarizes a study that reviewed research on business intelligence (BI) to support strategic decision making from 2010 to 2017. The review followed a systematic literature review process and analyzed 14 papers on BI. The review found that BI research has grown and followed technology trends over this period. Early papers discussed BI implementations in education and e-learning systems, while later papers examined BI in areas like call centers, healthcare, and small businesses. Frameworks for integrating BI with other systems like ERP were also proposed. Overall, the review showed the expanding scope and uses of BI in strategic decision support across different organizations and industries.
6. 17448 33940-1-ed 20 apr 13mar 28dec2018 ed iqbal qcIAESIJEECS
Business intelligence comprises of tools and applications that are leverages software and services to translate data into intelligent actions for strategic, tactical and operational decisions. The intelligent business solution facilitates and develops the service provided to the market researchers, saves time and effort needed to identify the customers predict demand and manage production more efficiently, ability to explore possibilities to increase revenue. The purpose of this paper is using business intelligence solutions for forecasting in Marketing Researches. The intelligence solutions are helping the market researchers to achieve efficiency, effectiveness, and differentiation.
Business intelligence (BI) is a system of tools and methods that aid in strategic planning and informed decision-making. This involves collecting data from internal and external sources, analyzing the data to gain insights, and visualizing insights for decision makers. BI helps organizations understand customer behavior, improve products and efficiency, gain competitive advantages, improve sales and marketing, and gain visibility across the organization. Determining if an organization needs BI involves assessing if the organization has data but no useful information, relies solely on IT for reports, or uses spreadsheets without dedicated BI software. Tracking the right metrics like quantitative vs qualitative, actionable vs vanity, reporting vs exploratory, correlated vs causal, and lagging vs leading metrics helps organizations focus on what
The need, applications, challenges, new trends and
a consulting perspective
(Why is Big Data a strategic need for optimization of organizational processes especially in the business domains and what is the consultant’s role?)
With every transaction and activity, organizations churn out data. This process happens even in the case of idle operation. Hence, data needs to be effectively analyzed to manage all processes better. Data can be used to make sense of the current situation and predict outcomes. It also can be used to optimize business processes and operations. This is easier said than done as data is being produced at an unprecedented rate, huge volumes and a high degree of variety. For the outcome of the data analysis to be relevant, all the data sets must be factored in to the analysis and predictions. This is where big data analysis comes in with its sophisticated tools that are also now easy on the pocket if one prefers the open source.
The future of high potential marketing lead generation would be based on big data. Virtually every business vertical can benefit from big data initiatives. Even those without deep pockets can use the cloud model for business analytics/big data analysis.
Some challenges remain to be addressed to engender large scale adoption but the current benefits outweigh the concerns.
India has seen a massive growth in big data adoption and the trend will grow though it is generally amongst the bigger players. As quality of data improves and customer reluctance to being honest when they volunteer data reduces, the forecasts will become more accurate and Big Data will have come to its rightful place as a key enabler.
Business analytics uses data to help organizations make better decisions and craft business strategies. As companies generate vast amounts of data, there is a need for professionals with data analysis skills. Leading companies are using analytics not just to improve operations but launch new business models. While some industries and digital natives have captured opportunities, much potential value from analytics remains untapped, especially in manufacturing, healthcare, and the public sector. For companies to succeed in an increasingly data-driven world, analytics must be incorporated strategically and supported by the right talent, processes, and infrastructure.
1. Data science involves applying scientific methods and processes to extract knowledge and insights from data. It includes techniques like machine learning, statistical analysis, and data visualization.
2. Data science has many applications in fields like marketing, healthcare, banking, and government. It helps with tasks like demand forecasting, fraud detection, personalized recommendations, and policymaking.
3. The key characteristics of data science include business understanding, intuition, curiosity, and skills in areas like machine learning algorithms, statistics, programming, and communication. Data scientists help organizations make better decisions using data-driven insights.
The document is a seminar report on business intelligence submitted by Gayatri Padhi. It discusses various topics related to business intelligence including its definition, components, issues, future, reasons for using it, and benefits. The report provides definitions of business intelligence from various experts and describes its key components such as data warehousing, data marts, OLAP, analytics and dashboards. It also discusses factors influencing business intelligence and how to design and implement effective BI systems.
Data Visualization Tools and Techniques for Datasets in Big DataIRJET Journal
This document discusses data visualization tools and techniques for datasets in big data. It begins by defining data analytics and the various types including social network analysis, business analytics, social media analytics, business impact analysis, and big data analytics. It then discusses data visualization and its uses in decision making, return on investment, information sharing, and time savings. Key aspects of big data visualization are described like real-time data analysis, dynamic nature, interactive presentations, being in-memory, and security. Common errors to avoid in data visualizations are also outlined. The document concludes by describing various data visualization tools that can be used for big data like Data Wrapper, Dygraphs, Chart JS, Charted, D3, Raw, Timeline,
4Emerging Trends in Business IntelligenceITS 531.docxblondellchancy
4
Emerging Trends in Business Intelligence
ITS 531-20 Business Intelligence
Emerging Trends in Business Intelligence
By
Vivek Reddy Chinthakuntla
Soumya Kalakonda
To Professor Dr. Kelly Bruning
University of the Cumberlands
Table of Contents
Abstract.......................................................................................................................................4
Business Intelligence with Data Analytics................................................................................................6
Partial Application of BI with Data Analytics...........................................................................................7
Future of BI and Data Analytics.................................................................................................................8
Positive and negative impacts of BI ..........................................................................................................9
Recommendations ....................................................................................................................................9
Cloud Computing with BI.......................................................................................................................10
Practical Implications..............................................................................................................................10
Future of Cloud Computing with BI........................................................................................................14
Advantages and Disadvantages................................................................................................................15
Recommendations....................................................................................................................................15
Introduction to Business Drive Data Intelligence.....................................................................................16
Data Governance of Self-Service BI ........................................................................................................19
Future of BI depends on Data Governance..............................................................................................19
Conclusion................................................................................................................................................20
References................................................................................................................................................ 22
Abstract:
This paper is based on the proposition used, and the outcomes attained, using data management to expedite the changes in the operation from a conventional old-fashioned practice to an automatic Business Intelligence data analytics system, presenting timely, reliable system production data by using Business Intelligence tools and technologies. This paper explains the importance and productivity of ...
Using data analytics to drive BI A case studyPhoenixraj
Using historical trip data from a bike share company, the study analyzed trends to help convert casual riders to annual members. Key findings include:
- Casual riders ride more on weekends while members prefer weekdays.
- Summer months see peak casual riding.
- The most used station, Streeter Dr & Grand Ave, had over 100,000 casual rides.
Recommendations include offering member incentives and discounts during peak casual riding periods, and partnering with local businesses near popular stations to advertise to casual riders. The study demonstrates how data analytics can provide business intelligence to improve marketing strategies.
How ‘Big Data’ Can Create Significant Impact on Enterprises? Part I: Findings...IJERA Editor
Big data is the latest buzz word in the BI domain, and is increasingly gaining traction amongst enterprises. The prospect of gaining highly targeted business and market insight from unmanageable and unstructured data sets is creating huge adoption potential for such solutions. The scope of big data moves beyond conventional enterprise databases to more open environments, covering new sources of information typically relating to various social networking sites, wikis and blogs. Moreover, advancements in communications and M2M technologies are also contributing to the massive availability of big data
Application business intelligence in railwaysVoice Malaysia
This document discusses business intelligence (BI) and its application in the railways market. BI refers to technologies and applications used to analyze business data in order to help companies make better decisions. The advantages of BI include improved data flow, implementing the right technologies, developing analytical talent, making fact-based decisions, increasing transparency, and fostering a culture of analytics. The document also provides examples of how BI has been applied successfully in the rail sector through dashboards and discusses some challenges of adopting BI.
This report is an outcome of research on topic 'Business Intelligence', which is a hot topic now. This research report is prepared for the partial fulfillment of the requirements for 'Current Developments Module' of B.Sc.Computing degree.
It demonstrates details of the Business Intelligence in today's world and explains BI architecture. It also provides detailed analysis on its use in the current business environment.
Data Visualization advances Business by promoting easy story-telling and info...IRJET Journal
1) The document discusses how data visualization advances business by promoting easy storytelling and informed decision-making using Microsoft Business Intelligence. It explores how data visualization serves as a transformative tool, facilitating seamless storytelling and informed decision-making through platforms like Microsoft BI.
2) The document proposes using data visualization tools across sales, finance, and marketing domains to simplify data understanding and enhance decision-making in today's data-driven business environment. Interactive dashboards are created using sample datasets from different business areas to demonstrate how data visualization benefits stakeholders and can be a reliable alternative for decision-making.
3) Insights from the interactive dashboards show how data visualization can provide key metrics and trends to stakeholders in different
This document summarizes a study that evaluated critical success factors for implementing a business intelligence (BI) system within an enterprise resource planning (ERP) environment at a cement manufacturing company in Indonesia. The study identified 13 success factors across 4 categories: organizational, process, technological, and environmental. Data was collected through literature review, expert interviews, and questionnaires. The Decision Making Trial and Evaluation Laboratory Model (DEMATEL) method was used to analyze the data and determine the most important factors in each category. The document provides context on BI and ERP systems and reviews literature on critical success factors for BI implementations.
Small and medium enterprise business solutions using data visualizationjournalBEEI
The small and medium enterprise (SME) companies optimize performance using different automated systems to highlight the operations concerns. However, lack of efficient visualization in reporting results in slow feedbacks, difficulties in extracting root cause, and minimal corrective actions. To complicate matters, the data heterogeneity has intensely increased, and it is produced in a fast manner making it unmanageable if the traditional methods of analytics are applied. Hence, we propose the use of a dashboard that can summarize the operational events using real-time data based on the data visualization approach. This proposed solution summarizes the raw data, which allows the user to make informed decisions that can give a positive impact on business performance. An interactive intelligent dashboard for SME (iid-SME) is developed to tackle issues such as measurement of cases completed, the duration of time needed to solve a case, the individual performance of handling cases and other tasks as a proof of concept. From the result, the implementation of the iid-SME approach simplifies the conveyance of the message and helps the SME personnel to make decisions. With the positive feedback obtained, it is envisaged that such a solution can be further employed for SME improvement for better profit and decision making.
Business intelligence and IT governance are increasingly important for modern businesses. Business intelligence involves collecting and analyzing large amounts of data to help businesses make better decisions. It has evolved from early attempts by businesses to understand their own information and markets. Modern business intelligence utilizes tools like dashboards, scorecards, and data warehouses. IT governance ensures that business and IT strategies are aligned and that information technology supports business objectives. Business intelligence 2.0 takes analysis a step further by enabling more interactive and flexible analysis of both structured and unstructured data.
Similar to PREDICTIVE BUSINESS INTELLIGENCE: CONSUMER GOODS SALES FORECASTING USING ARTIFICIAL NEURAL NETWORK (20)
Submission Deadline: 30th September 2022
Acceptance Notification: Within Three Days’ time period
Online Publication: Within 24 Hrs. time Period
Expected Date of Dispatch of Printed Journal: 5th October 2022
MODELING AND ANALYSIS OF SURFACE ROUGHNESS AND WHITE LATER THICKNESS IN WIRE-...IAEME Publication
White layer thickness (WLT) formed and surface roughness in wire electric discharge turning (WEDT) of tungsten carbide composite has been made to model through response surface methodology (RSM). A Taguchi’s standard Design of experiments involving five input variables with three levels has been employed to establish a mathematical model between input parameters and responses. Percentage of cobalt content, spindle speed, Pulse on-time, wire feed and pulse off-time were changed during the experimental tests based on the Taguchi’s orthogonal array L27 (3^13). Analysis of variance (ANOVA) revealed that the mathematical models obtained can adequately describe performance within the parameters of the factors considered. There was a good agreement between the experimental and predicted values in this study.
A STUDY ON THE REASONS FOR TRANSGENDER TO BECOME ENTREPRENEURSIAEME Publication
The study explores the reasons for a transgender to become entrepreneurs. In this study transgender entrepreneur was taken as independent variable and reasons to become as dependent variable. Data were collected through a structured questionnaire containing a five point Likert Scale. The study examined the data of 30 transgender entrepreneurs in Salem Municipal Corporation of Tamil Nadu State, India. Simple Random sampling technique was used. Garrett Ranking Technique (Percentile Position, Mean Scores) was used as the analysis for the present study to identify the top 13 stimulus factors for establishment of trans entrepreneurial venture. Economic advancement of a nation is governed upon the upshot of a resolute entrepreneurial doings. The conception of entrepreneurship has stretched and materialized to the socially deflated uncharted sections of transgender community. Presently transgenders have smashed their stereotypes and are making recent headlines of achievements in various fields of our Indian society. The trans-community is gradually being observed in a new light and has been trying to achieve prospective growth in entrepreneurship. The findings of the research revealed that the optimistic changes are taking place to change affirmative societal outlook of the transgender for entrepreneurial ventureship. It also laid emphasis on other transgenders to renovate their traditional living. The paper also highlights that legislators, supervisory body should endorse an impartial canons and reforms in Tamil Nadu Transgender Welfare Board Association.
BROAD UNEXPOSED SKILLS OF TRANSGENDER ENTREPRENEURSIAEME Publication
Since ages gender difference is always a debatable theme whether caused by nature, evolution or environment. The birth of a transgender is dreadful not only for the child but also for their parents. The pain of living in the wrong physique and treated as second class victimized citizen is outrageous and fully harboured with vicious baseless negative scruples. For so long, social exclusion had perpetuated inequality and deprivation experiencing ingrained malign stigma and besieged victims of crime or violence across their life spans. They are pushed into the murky way of life with a source of eternal disgust, bereft sexual potency and perennial fear. Although they are highly visible but very little is known about them. The common public needs to comprehend the ravaged arrogance on these insensitive souls and assist in integrating them into the mainstream by offering equal opportunity, treat with humanity and respect their dignity. Entrepreneurship in the current age is endorsing the gender fairness movement. Unstable careers and economic inadequacy had inclined one of the gender variant people called Transgender to become entrepreneurs. These tiny budding entrepreneurs resulted in economic transition by means of employment, free from the clutches of stereotype jobs, raised standard of living and handful of financial empowerment. Besides all these inhibitions, they were able to witness a platform for skill set development that ignited them to enter into entrepreneurial domain. This paper epitomizes skill sets involved in trans-entrepreneurs of Thoothukudi Municipal Corporation of Tamil Nadu State and is a groundbreaking determination to sightsee various skills incorporated and the impact on entrepreneurship.
DETERMINANTS AFFECTING THE USER'S INTENTION TO USE MOBILE BANKING APPLICATIONSIAEME Publication
The banking and financial services industries are experiencing increased technology penetration. Among them, the banking industry has made technological advancements to better serve the general populace. The economy focused on transforming the banking sector's system into a cashless, paperless, and faceless one. The researcher wants to evaluate the user's intention for utilising a mobile banking application. The study also examines the variables affecting the user's behaviour intention when selecting specific applications for financial transactions. The researcher employed a well-structured questionnaire and a descriptive study methodology to gather the respondents' primary data utilising the snowball sampling technique. The study includes variables like performance expectations, effort expectations, social impact, enabling circumstances, and perceived risk. Each of the aforementioned variables has a major impact on how users utilise mobile banking applications. The outcome will assist the service provider in comprehending the user's history with mobile banking applications.
ANALYSE THE USER PREDILECTION ON GPAY AND PHONEPE FOR DIGITAL TRANSACTIONSIAEME Publication
Technology upgradation in banking sector took the economy to view that payment mode towards online transactions using mobile applications. This system enabled connectivity between banks, Merchant and user in a convenient mode. there are various applications used for online transactions such as Google pay, Paytm, freecharge, mobikiwi, oxygen, phonepe and so on and it also includes mobile banking applications. The study aimed at evaluating the predilection of the user in adopting digital transaction. The study is descriptive in nature. The researcher used random sample techniques to collect the data. The findings reveal that mobile applications differ with the quality of service rendered by Gpay and Phonepe. The researcher suggest the Phonepe application should focus on implementing the application should be user friendly interface and Gpay on motivating the users to feel the importance of request for money and modes of payments in the application.
VOICE BASED ATM FOR VISUALLY IMPAIRED USING ARDUINOIAEME Publication
The prototype of a voice-based ATM for visually impaired using Arduino is to help people who are blind. This uses RFID cards which contain users fingerprint encrypted on it and interacts with the users through voice commands. ATM operates when sensor detects the presence of one person in the cabin. After scanning the RFID card, it will ask to select the mode like –normal or blind. User can select the respective mode through voice input, if blind mode is selected the balance check or cash withdraw can be done through voice input. Normal mode procedure is same as the existing ATM.
IMPACT OF EMOTIONAL INTELLIGENCE ON HUMAN RESOURCE MANAGEMENT PRACTICES AMONG...IAEME Publication
There is increasing acceptability of emotional intelligence as a major factor in personality assessment and effective human resource management. Emotional intelligence as the ability to build capacity, empathize, co-operate, motivate and develop others cannot be divorced from both effective performance and human resource management systems. The human person is crucial in defining organizational leadership and fortunes in terms of challenges and opportunities and walking across both multinational and bilateral relationships. The growing complexity of the business world requires a great deal of self-confidence, integrity, communication, conflict and diversity management to keep the global enterprise within the paths of productivity and sustainability. Using the exploratory research design and 255 participants the result of this original study indicates strong positive correlation between emotional intelligence and effective human resource management. The paper offers suggestions on further studies between emotional intelligence and human capital development and recommends for conflict management as an integral part of effective human resource management.
VISUALISING AGING PARENTS & THEIR CLOSE CARERS LIFE JOURNEY IN AGING ECONOMYIAEME Publication
Our life journey, in general, is closely defined by the way we understand the meaning of why we coexist and deal with its challenges. As we develop the "inspiration economy", we could say that nearly all of the challenges we have faced are opportunities that help us to discover the rest of our journey. In this note paper, we explore how being faced with the opportunity of being a close carer for an aging parent with dementia brought intangible discoveries that changed our insight of the meaning of the rest of our life journey.
A STUDY ON THE IMPACT OF ORGANIZATIONAL CULTURE ON THE EFFECTIVENESS OF PERFO...IAEME Publication
The main objective of this study is to analyze the impact of aspects of Organizational Culture on the Effectiveness of the Performance Management System (PMS) in the Health Care Organization at Thanjavur. Organizational Culture and PMS play a crucial role in present-day organizations in achieving their objectives. PMS needs employees’ cooperation to achieve its intended objectives. Employees' cooperation depends upon the organization’s culture. The present study uses exploratory research to examine the relationship between the Organization's culture and the Effectiveness of the Performance Management System. The study uses a Structured Questionnaire to collect the primary data. For this study, Thirty-six non-clinical employees were selected from twelve randomly selected Health Care organizations at Thanjavur. Thirty-two fully completed questionnaires were received.
Living in 21st century in itself reminds all of us the necessity of police and its administration. As more and more we are entering into the modern society and culture, the more we require the services of the so called ‘Khaki Worthy’ men i.e., the police personnel. Whether we talk of Indian police or the other nation’s police, they all have the same recognition as they have in India. But as already mentioned, their services and requirements are different after the like 26th November, 2008 incidents, where they without saving their own lives has sacrificed themselves without any hitch and without caring about their respective family members and wards. In other words, they are like our heroes and mentors who can guide us from the darkness of fear, militancy, corruption and other dark sides of life and so on. Now the question arises, if Gandhi would have been alive today, what would have been his reaction/opinion to the police and its functioning? Would he have some thing different in his mind now what he had been in his mind before the partition or would he be going to start some Satyagraha in the form of some improvement in the functioning of the police administration? Really these questions or rather night mares can come to any one’s mind, when there is too much confusion is prevailing in our minds, when there is too much corruption in the society and when the polices working is also in the questioning because of one or the other case throughout the India. It is matter of great concern that we have to thing over our administration and our practical approach because the police personals are also like us, they are part and parcel of our society and among one of us, so why we all are pin pointing towards them.
A STUDY ON TALENT MANAGEMENT AND ITS IMPACT ON EMPLOYEE RETENTION IN SELECTED...IAEME Publication
The goal of this study was to see how talent management affected employee retention in the selected IT organizations in Chennai. The fundamental issue was the difficulty to attract, hire, and retain talented personnel who perform well and the gap between supply and demand of talent acquisition and retaining them within the firms. The study's main goals were to determine the impact of talent management on employee retention in IT companies in Chennai, investigate talent management strategies that IT companies could use to improve talent acquisition, performance management, career planning and formulate retention strategies that the IT firms could use. The respondents were given a structured close-ended questionnaire with the 5 Point Likert Scale as part of the study's quantitative research design. The target population consisted of 289 IT professionals. The questionnaires were distributed and collected by the researcher directly. The Statistical Package for Social Sciences (SPSS) was used to collect and analyse the questionnaire responses. Hypotheses that were formulated for the various areas of the study were tested using a variety of statistical tests. The key findings of the study suggested that talent management had an impact on employee retention. The studies also found that there is a clear link between the implementation of talent management and retention measures. Management should provide enough training and development for employees, clarify job responsibilities, provide adequate remuneration packages, and recognise employees for exceptional performance.
ATTRITION IN THE IT INDUSTRY DURING COVID-19 PANDEMIC: LINKING EMOTIONAL INTE...IAEME Publication
Globally, Millions of dollars were spent by the organizations for employing skilled Information Technology (IT) professionals. It is costly to replace unskilled employees with IT professionals possessing technical skills and competencies that aid in interconnecting the business processes. The organization’s employment tactics were forced to alter by globalization along with technological innovations as they consistently diminish to remain lean, outsource to concentrate on core competencies along with restructuring/reallocate personnel to gather efficiency. As other jobs, organizations or professions have become reasonably more appropriate in a shifting employment landscape, the above alterations trigger both involuntary as well as voluntary turnover. The employee view on jobs is also afflicted by the COVID-19 pandemic along with the employee-driven labour market. So, having effective strategies is necessary to tackle the withdrawal rate of employees. By associating Emotional Intelligence (EI) along with Talent Management (TM) in the IT industry, the rise in attrition rate was analyzed in this study. Only 303 respondents were collected out of 350 participants to whom questionnaires were distributed. From the employees of IT organizations located in Bangalore (India), the data were congregated. A simple random sampling methodology was employed to congregate data as of the respondents. Generating the hypothesis along with testing is eventuated. The effect of EI and TM along with regression analysis between TM and EI was analyzed. The outcomes indicated that employee and Organizational Performance (OP) were elevated by effective EI along with TM.
INFLUENCE OF TALENT MANAGEMENT PRACTICES ON ORGANIZATIONAL PERFORMANCE A STUD...IAEME Publication
By implementing talent management strategy, organizations would have the option to retain their skilled professionals while additionally working on their overall performance. It is the course of appropriately utilizing the ideal individuals, setting them up for future top positions, exploring and dealing with their performance, and holding them back from leaving the organization. It is employee performance that determines the success of every organization. The firm quickly obtains an upper hand over its rivals in the event that its employees having particular skills that cannot be duplicated by the competitors. Thus, firms are centred on creating successful talent management practices and processes to deal with the unique human resources. Firms are additionally endeavouring to keep their top/key staff since on the off chance that they leave; the whole store of information leaves the firm's hands. The study's objective was to determine the impact of talent management on organizational performance among the selected IT organizations in Chennai. The study recommends that talent management limitedly affects performance. On the off chance that this talent is appropriately management and implemented properly, organizations might benefit as much as possible from their maintained assets to support development and productivity, both monetarily and non-monetarily.
A STUDY OF VARIOUS TYPES OF LOANS OF SELECTED PUBLIC AND PRIVATE SECTOR BANKS...IAEME Publication
Banking regulations act of India, 1949 defines banking as “acceptance of deposits for the purpose of lending or investment from the public, repayment on demand or otherwise and withdrawable through cheques, drafts order or otherwise”, the major participants of the Indian financial system are commercial banks, the financial institution encompassing term lending institutions. Investments institutions, specialized financial institution and the state level development banks, non banking financial companies (NBFC) and other market intermediaries such has the stock brokers and money lenders are among the oldest of the certain variants of NBFC and the oldest market participants. The asset quality of banks is one of the most important indicators of their financial health. The Indian banking sector has been facing severe problems of increasing Non- Performing Assets (NPAs). The NPAs growth directly and indirectly affects the quality of assets and profitability of banks. It also shows the efficiency of banks credit risk management and the recovery effectiveness. NPA do not generate any income, whereas, the bank is required to make provisions for such as assets that why is a double edge weapon. This paper outlines the concept of quality of bank loans of different types like Housing, Agriculture and MSME loans in state Haryana of selected public and private sector banks. This study is highlighting problems associated with the role of commercial bank in financing Small and Medium Scale Enterprises (SME). The overall objective of the research was to assess the effect of the financing provisions existing for the setting up and operations of MSMEs in the country and to generate recommendations for more robust financing mechanisms for successful operation of the MSMEs, in turn understanding the impact of MSME loans on financial institutions due to NPA. There are many research conducted on the topic of Non- Performing Assets (NPA) Management, concerning particular bank, comparative study of public and private banks etc. In this paper the researcher is considering the aggregate data of selected public sector and private sector banks and attempts to compare the NPA of Housing, Agriculture and MSME loans in state Haryana of public and private sector banks. The tools used in the study are average and Anova test and variance. The findings reveal that NPA is common problem for both public and private sector banks and is associated with all types of loans either that is housing loans, agriculture loans and loans to SMES. NPAs of both public and private sector banks show the increasing trend. In 2010-11 GNPA of public and private sector were at same level it was 2% but after 2010-11 it increased in many fold and at present there is GNPA in some more than 15%. It shows the dark area of Indian banking sector.
EXPERIMENTAL STUDY OF MECHANICAL AND TRIBOLOGICAL RELATION OF NYLON/BaSO4 POL...IAEME Publication
An experiment conducted in this study found that BaSO4 changed Nylon 6's mechanical properties. By changing the weight ratios, BaSO4 was used to make Nylon 6. This Researcher looked into how hard Nylon-6/BaSO4 composites are and how well they wear. Experiments were done based on Taguchi design L9. Nylon-6/BaSO4 composites can be tested for their hardness number using a Rockwell hardness testing apparatus. On Nylon/BaSO4, the wear behavior was measured by a wear monitor, pinon-disc friction by varying reinforcement, sliding speed, and sliding distance, and the microstructure of the crack surfaces was observed by SEM. This study provides significant contributions to ultimate strength by increasing BaSO4 content up to 16% in the composites, and sliding speed contributes 72.45% to the wear rate
ROLE OF SOCIAL ENTREPRENEURSHIP IN RURAL DEVELOPMENT OF INDIA - PROBLEMS AND ...IAEME Publication
The majority of the population in India lives in villages. The village is the back bone of the country. Village or rural industries play an important role in the national economy, particularly in the rural development. Developing the rural economy is one of the key indicators towards a country’s success. Whether it be the need to look after the welfare of the farmers or invest in rural infrastructure, Governments have to ensure that rural development isn’t compromised. The economic development of our country largely depends on the progress of rural areas and the standard of living of rural masses. Village or rural industries play an important role in the national economy, particularly in the rural development. Rural entrepreneurship is based on stimulating local entrepreneurial talent and the subsequent growth of indigenous enterprises. It recognizes opportunity in the rural areas and accelerates a unique blend of resources either inside or outside of agriculture. Rural entrepreneurship brings an economic value to the rural sector by creating new methods of production, new markets, new products and generate employment opportunities thereby ensuring continuous rural development. Social Entrepreneurship has the direct and primary objective of serving the society along with the earning profits. So, social entrepreneurship is different from the economic entrepreneurship as its basic objective is not to earn profits but for providing innovative solutions to meet the society needs which are not taken care by majority of the entrepreneurs as they are in the business for profit making as a sole objective. So, the Social Entrepreneurs have the huge growth potential particularly in the developing countries like India where we have huge societal disparities in terms of the financial positions of the population. Still 22 percent of the Indian population is below the poverty line and also there is disparity among the rural & urban population in terms of families living under BPL. 25.7 percent of the rural population & 13.7 percent of the urban population is under BPL which clearly shows the disparity of the poor people in the rural and urban areas. The need to develop social entrepreneurship in agriculture is dictated by a large number of social problems. Such problems include low living standards, unemployment, and social tension. The reasons that led to the emergence of the practice of social entrepreneurship are the above factors. The research problem lays upon disclosing the importance of role of social entrepreneurship in rural development of India. The paper the tendencies of social entrepreneurship in India, to present successful examples of such business for providing recommendations how to improve situation in rural areas in terms of social entrepreneurship development. Indian government has made some steps towards development of social enterprises, social entrepreneurship, and social in- novation, but a lot remains to be improved.
OPTIMAL RECONFIGURATION OF POWER DISTRIBUTION RADIAL NETWORK USING HYBRID MET...IAEME Publication
Distribution system is a critical link between the electric power distributor and the consumers. Most of the distribution networks commonly used by the electric utility is the radial distribution network. However in this type of network, it has technical issues such as enormous power losses which affect the quality of the supply. Nowadays, the introduction of Distributed Generation (DG) units in the system help improve and support the voltage profile of the network as well as the performance of the system components through power loss mitigation. In this study network reconfiguration was done using two meta-heuristic algorithms Particle Swarm Optimization and Gravitational Search Algorithm (PSO-GSA) to enhance power quality and voltage profile in the system when simultaneously applied with the DG units. Backward/Forward Sweep Method was used in the load flow analysis and simulated using the MATLAB program. Five cases were considered in the Reconfiguration based on the contribution of DG units. The proposed method was tested using IEEE 33 bus system. Based on the results, there was a voltage profile improvement in the system from 0.9038 p.u. to 0.9594 p.u.. The integration of DG in the network also reduced power losses from 210.98 kW to 69.3963 kW. Simulated results are drawn to show the performance of each case.
APPLICATION OF FRUGAL APPROACH FOR PRODUCTIVITY IMPROVEMENT - A CASE STUDY OF...IAEME Publication
Manufacturing industries have witnessed an outburst in productivity. For productivity improvement manufacturing industries are taking various initiatives by using lean tools and techniques. However, in different manufacturing industries, frugal approach is applied in product design and services as a tool for improvement. Frugal approach contributed to prove less is more and seems indirectly contributing to improve productivity. Hence, there is need to understand status of frugal approach application in manufacturing industries. All manufacturing industries are trying hard and putting continuous efforts for competitive existence. For productivity improvements, manufacturing industries are coming up with different effective and efficient solutions in manufacturing processes and operations. To overcome current challenges, manufacturing industries have started using frugal approach in product design and services. For this study, methodology adopted with both primary and secondary sources of data. For primary source interview and observation technique is used and for secondary source review has done based on available literatures in website, printed magazines, manual etc. An attempt has made for understanding application of frugal approach with the study of manufacturing industry project. Manufacturing industry selected for this project study is Mahindra and Mahindra Ltd. This paper will help researcher to find the connections between the two concepts productivity improvement and frugal approach. This paper will help to understand significance of frugal approach for productivity improvement in manufacturing industry. This will also help to understand current scenario of frugal approach in manufacturing industry. In manufacturing industries various process are involved to deliver the final product. In the process of converting input in to output through manufacturing process productivity plays very critical role. Hence this study will help to evolve status of frugal approach in productivity improvement programme. The notion of frugal can be viewed as an approach towards productivity improvement in manufacturing industries.
A MULTIPLE – CHANNEL QUEUING MODELS ON FUZZY ENVIRONMENTIAEME Publication
In this paper, we investigated a queuing model of fuzzy environment-based a multiple channel queuing model (M/M/C) ( /FCFS) and study its performance under realistic conditions. It applies a nonagonal fuzzy number to analyse the relevant performance of a multiple channel queuing model (M/M/C) ( /FCFS). Based on the sub interval average ranking method for nonagonal fuzzy number, we convert fuzzy number to crisp one. Numerical results reveal that the efficiency of this method. Intuitively, the fuzzy environment adapts well to a multiple channel queuing models (M/M/C) ( /FCFS) are very well.
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
CHINA’S GEO-ECONOMIC OUTREACH IN CENTRAL ASIAN COUNTRIES AND FUTURE PROSPECTjpsjournal1
The rivalry between prominent international actors for dominance over Central Asia's hydrocarbon
reserves and the ancient silk trade route, along with China's diplomatic endeavours in the area, has been
referred to as the "New Great Game." This research centres on the power struggle, considering
geopolitical, geostrategic, and geoeconomic variables. Topics including trade, political hegemony, oil
politics, and conventional and nontraditional security are all explored and explained by the researcher.
Using Mackinder's Heartland, Spykman Rimland, and Hegemonic Stability theories, examines China's role
in Central Asia. This study adheres to the empirical epistemological method and has taken care of
objectivity. This study analyze primary and secondary research documents critically to elaborate role of
china’s geo economic outreach in central Asian countries and its future prospect. China is thriving in trade,
pipeline politics, and winning states, according to this study, thanks to important instruments like the
Shanghai Cooperation Organisation and the Belt and Road Economic Initiative. According to this study,
China is seeing significant success in commerce, pipeline politics, and gaining influence on other
governments. This success may be attributed to the effective utilisation of key tools such as the Shanghai
Cooperation Organisation and the Belt and Road Economic Initiative.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
Harnessing WebAssembly for Real-time Stateless Streaming PipelinesChristina Lin
Traditionally, dealing with real-time data pipelines has involved significant overhead, even for straightforward tasks like data transformation or masking. However, in this talk, we’ll venture into the dynamic realm of WebAssembly (WASM) and discover how it can revolutionize the creation of stateless streaming pipelines within a Kafka (Redpanda) broker. These pipelines are adept at managing low-latency, high-data-volume scenarios.
Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapte...University of Maribor
Slides from talk presenting:
Aleš Zamuda: Presentation of IEEE Slovenia CIS (Computational Intelligence Society) Chapter and Networking.
Presentation at IcETRAN 2024 session:
"Inter-Society Networking Panel GRSS/MTT-S/CIS
Panel Session: Promoting Connection and Cooperation"
IEEE Slovenia GRSS
IEEE Serbia and Montenegro MTT-S
IEEE Slovenia CIS
11TH INTERNATIONAL CONFERENCE ON ELECTRICAL, ELECTRONIC AND COMPUTING ENGINEERING
3-6 June 2024, Niš, Serbia
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
A SYSTEMATIC RISK ASSESSMENT APPROACH FOR SECURING THE SMART IRRIGATION SYSTEMSIJNSA Journal
The smart irrigation system represents an innovative approach to optimize water usage in agricultural and landscaping practices. The integration of cutting-edge technologies, including sensors, actuators, and data analysis, empowers this system to provide accurate monitoring and control of irrigation processes by leveraging real-time environmental conditions. The main objective of a smart irrigation system is to optimize water efficiency, minimize expenses, and foster the adoption of sustainable water management methods. This paper conducts a systematic risk assessment by exploring the key components/assets and their functionalities in the smart irrigation system. The crucial role of sensors in gathering data on soil moisture, weather patterns, and plant well-being is emphasized in this system. These sensors enable intelligent decision-making in irrigation scheduling and water distribution, leading to enhanced water efficiency and sustainable water management practices. Actuators enable automated control of irrigation devices, ensuring precise and targeted water delivery to plants. Additionally, the paper addresses the potential threat and vulnerabilities associated with smart irrigation systems. It discusses limitations of the system, such as power constraints and computational capabilities, and calculates the potential security risks. The paper suggests possible risk treatment methods for effective secure system operation. In conclusion, the paper emphasizes the significant benefits of implementing smart irrigation systems, including improved water conservation, increased crop yield, and reduced environmental impact. Additionally, based on the security analysis conducted, the paper recommends the implementation of countermeasures and security approaches to address vulnerabilities and ensure the integrity and reliability of the system. By incorporating these measures, smart irrigation technology can revolutionize water management practices in agriculture, promoting sustainability, resource efficiency, and safeguarding against potential security threats.
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presentation of reports, and fast that is, cut down on the time for making the usual report. PT.
X also has problems in presenting reports that have complex indicators that require high
accuracy in their presentation, even though these reports are very crucial for stakeholders.
In addition, there are several product sales reports that are still done manually by the Sales
Business Unit in PT. X, for example sales turnover reports per item, best-selling product
reports per period, turnover reports per branch, and others. In addition to taking time to make
the report, the report presented is minimal visualization because it is only presented in the
form of a simple table so that it will be difficult to analyze, Other problems report presented at
PT. The X is done manually by creating a query in the OLTP / Online Transaction Processing
database, then the results are processed using Excel macros. To maintain the business of PT.
X remains in the best performance, it needs a business intelligence design and a good method
of analysis. The method proposed by the author is a method that can be used to predict sales
value based on existing sales data (sales forecasting).
By implementing Business Intelligence and data mining, companies can learn from the
data that has been collected, can evaluate the performance of the sales department, can
understand market trends from the products sold, and can predict future sales levels. In
addition, Business Intelligence can display detailed transaction data recapitulation quickly.
2. RELATED WORKS
Previously, many researchers had conducted research on Business Intelligence. The following
are some of the studies that have been conducted relating to the application of Business
Intelligence. In [1] Negash proposed a Business Intelligence framework and also identified
potential research areas. The BI Framework highlights the importance of semi-structured data
to support decision making, in addition discusses matrices for BI data types (structured vs.
semi structured) and source data (internal vs. external) to guide future research. According to
him, many BI Tools exist for acquisition, integration, cleaning, searching, analyzing, and
sending structured data for analysis and decision making, but further research is needed to
integrate these bi tools and to provide actionable information.
The next three years, to be exact in 2007, according to [2] Olszak described the process of
building a Business Intelligence system and proposing a methodology of making and
implementing an organizational system. The approach involves two stages, that is the BI
Creation and BI Consumption. BI Creation is the most time consuming stage and this stage
requires the largest share of financial and labor resources in the BI cycle, this phase consists
of several stages, that is the BI business definition, such as the determination of the BI system
development strategy, identifying and preparing data sources, choose Tools BI, design and
implement BI, and find and explore new information needs and other business applications.
Stage BI Consumption is related to end user users, this stage can be divided into several
different steps that must be taken based on the user's wisdom and in accordance with the
needs or tasks that must be faced. The steps mainly include:
1) Logistics analysis that allows to quickly identify supply chain partners
2) Access, monitoring and analysis of facts
3) Development of alternative decisions
4) Distribution and cooperation
5) Changes in the influence of company performance
The BI system must be independent of its hardware and software platform, BI solutions
should be flexible, once business changes, organizations must adjust the BI system to new
conditions, BI solutions must be measurable, and the BI system must be based on modern
technology. In addition to the researchers mentioned above, there are also researchers who
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conducted research concerning Business Intelligence conducted in 2010, in [3] Hawking
conducted a research which aims to determine the determinants of success associated with BI
in an ERP system environment. In his research, used qualitative methods to investigate
critical success factors associated with BI adoption. Hawking et al collected samples for
analysis whose contents consisted of industry presentations sourced from 69 industries related
to SAP. And from the sample results it was concluded that several important factors in
determining the success of BI, specially Management Support, Resources, User Participation,
Team Skills, Source Systems, and Development Technology.
In 2015, [4] Joshi conducted research on data mining techniques to increase the
effectiveness of sales and marketing. The method used is K-Means Clustering & Most
Frequent Pattern. In this research proposed a system for doing sales forecasting which
consists of 2 phases. The first phase is to divide stock data in 3 different product categories,
that is Dead Stock, Slow Moving, and Fast Moving by using K-Means. The second phase uses
the Most Frequent Pattern to find frequent item attribute patterns in each product category that
has been Clusters in the first phase and provide sales trends in a concise form.
In the same year [5] Katkar conducted research in the same field, namely sales
forecasting, but with a different method, specifically using the Naïve Bayesian Classifier
approach. It is proposed a system that could classify sales of products into categories such as
Poor, Average, and Good. If the product estimate is Good, the system will provide a hint
stating that sufficient stock must be available. Then in 2016, [6] Vhatkar conducted a Sales
Forecasting study using Artificial Neural Network Models. This study explains the
forecasting method in detail. Oral Care Products sales are predicted with the help of the Back
Propagation Learning algorithm and the accuracy of the forecast is validated. Error
Calculation is also observed using Mean Absolute Deviation, Mean Squared Error, and Root
Mean Square Error.
The conclusion that can be drawn from the previous studies described above is that
Business Intelligence is growing along with technological developments, Business
Intelligence is no longer just a means of data visualization, but BI components are also able to
be used for data exploration and data mining solutions including Forecasting, Market
Basketball Analysis, Sequence Analysis, Neural Networks, and others. By utilizing a
combination of Business Intelligence and Data Mining, the solution from Business
Intelligence can be better than simply displaying data without the exploration of the data.
3. METHODOLOGY
3.1 Data warehouse
The data warehouse design method that will be used in this research is the Kimball Lifecycle
Method, [7] which is a bottom-up approach, starting with a data mart, data flowing from the
source into the data mart and then formed into a data warehouse, and implemented in stages.
There are 9 steps from the Kimball Lifecycle method, [8] which is often referred to as nine-
step methodology.
Choose The Process: Sales Data to evaluate sales performance and achievement of
sales turnover at PT. X
Choose The Grains: Sales Invoice
Identify and Conform the Dimensions: Period, Site, Product, Strata Customer, Sales,
and Team Sales Dimensions
Choose the fact: The facts chosen from this case study are sales facts, where the
measures in this table include qty and nominal turnover, targets and achievements of
each target type
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Store Pre-calculations in fact table: At this stage, the result of the calculation is the
total = price x quantity is not displayed
Round out the dimension table: At this stage, the dimensions that have been defined
will be made a description containing structured information about the attributes of
these dimensions
Choose the duration of database: The data that will be entered is data for the last year,
starting from Jan 2017 to Sep 2018
Tracking Slowly Changing Dimensions: This stage aims to overcome dimensions that
can change slowly and can become problems.
There are 3 responses to this case, that is Overwrite, add new dimension records, and
add new fields
Decide The Physical Design: This stage is the physical design stage of a data
warehouse. At this stage the ETL process is also carried out
Figure 1 is a star schema for designing the proposed data warehouse
Figure 1. Star Schema for Proposed Data Warehouse
3.2. Artificial Neural Network
The algorithm used for sales prediction in this study is backpropagation neural network
(BPNN), [9] below is the architecture of the BPNN algorithm
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Figure 2. BPNN Architecture
Stages of the BPNN Algorithm [10]:
Initialization Stage
Step 0:
Initialize the connection weights between neurons using small random numbers (-0.5
to +0.5) and the rate of learning (α)
Step 1:
Do step 2 until step 9 as long as the specified stop condition is not met
Step 2:
Do step 3 through step 8 for each training pair.
Forward Propagation Stage
Step 3:
[11]
Each input neuron (Xi) receives an input signal xi, and spreads it to all neurons in the
hidden layer.
Step 4:
Each neuron in the hidden layer adds up all incoming signals.
[12]
Each neuron in the hidden layer uses an activation function to
produce an output signal
Step 5:
Each neuron in the output layer sums up all incoming signals.
Each neuron in the output layer uses an activation function to produce an output
signal.
[13]
Back propagation stage
Step 6:
Each neuron in the output layer calculates the error information between the signals
produced with the target pattern
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Calculate weight correction:
Calculate bias correction: [14]
Step 7:
Each neuron in the hidden layer adds up all incoming signals
Each neuron in the hidden layer calculates error information
Calculate weight correction:
Calculate bias correction: [15]
Adjustment of weights
Step 8:
Update weights and bias on relationships between layers.
Step 9:
Check the stop condition [16]
BPNN will be applied in this study by entering input parameters obtained from the data
warehouse that has been made. There are several stages in implementing BPNN in this study,
including:
1. Prepare a dataset
In this stage, a dataset will be prepared from the data warehouse, the dataset used will be an
aggregation of sales facts and other dimensions that will be grouped by province and based on
the month of the year so that the time-series dataset is obtained. The dataset, which initially
consists of millions of rows of transactions of around 6 million rows, will be simplified to
around 800 rows at this stage.
2. Selection of attributes
Attribute selection activities are used to separate the prediction target with the attributes that
become the variables in this study. In this dataset that will be predicted is revenue in units of
Rupiah, while other attributes will be variable. Table 1 below shows the attributes in this
dataset.
Table 1. Dataset Attributes
Attribute Name Information
Province List of provinces in data warehouse
(consisting of 20 provinces)
Period The period used is in the format of the
month and year
Revenue Rp Total turnover in rupiah units, this
attribute that will be the target
prediction
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Revenue Qty The total items sold in carton units
Rupiah Return Total return in units of rupiah
Quantity Return The total items return in carton units
3. Application of Algorithms
At this stage the BPNN algorithm will be implemented in this dataset. The features will pass
through the phases of the BPNN algorithm starting from initialization, forward propagation,
back propagation, and weight adjustment, so that the predicted value is generated. All of these
phases will be built using the help of Rapid miner tools
4. RESULT AND ANALYSIS
Figure 3 shows variation in solar intensity for different days when mass flow rate of The
results of the case study included the conduct of ETL processes from the star schema that had
been designed, the results of the data warehouse were imported into BI tools, namely Qlik
Sense and Business Intelligence was designed. Business Intelligence that is built includes a
sales dashboard, this dashboard displays revenue distribution maps, the top 10 provinces
supporting revenue, the top 20 best-selling product categories per region, and a graph of
revenue growth against targets. The designed Sales Dashboard is displayed through the image
below.
Figure 3. Sales Dashboard
Analysis that can be delivered from the dashboard that has been made includes:
- Provinces that have large revenue contributions have not evenly distributed, the eastern
region of Indonesia has not contributed maximally
- Achievement of targets is still low, can be seen every month many regions do not reach the
target given
- There is one product that dominates sales, its value is far from other products
- Predictions generated using the BPNN algorithm method have movements that follow the
flow of real revenue movements. Prediction results can be used as a reference or preparation
before the sales go into the field.
The strategies that need to be taken by the company from the analysis:
- Also paying attention to the region are still not contributing maximally to revenue, by
increasing the number of sales and raising market campaigns in the region.
8. Yulyardo and Sani M. Isa
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- Providing a reasonable target that can be achieved by the salesmen, can be obtained for
example from the prediction results that have been made, it can also be by providing
opportunities for salesmen to get incentives that spur salesmen's desire to reach the target.
- Conduct a survey directly to the market to test whether there is one product that is only sold
in an area and is not sold in other regions, so there needs to be a review to sell products that
are in line with market segmentation.
In addition, this case study also carries the prediction of revenue made with revenue
datasets that have been grouped by province per month. The total data collected which
previously amounted to 6 million of rows was compressed to around 800 rows because it had
been aggregated. The data is time-series data that has been aggregated per province and per
month, the data consists of the code and name of the province, period per month, Revenue
Rupiah, Quantity Revenue, Rupiah Return, Quantity Return, and number of salesmen.
The dataset is then imported into rapid miner, and prediction modeling is performed.
Because the data is in the form of time series data, the windowing method is carried out,
which is to map period attributes into features. In this case study, the windowing parameter is
6, so in other words revenue prediction is the result of revenues 6 months before. After the
windowing process, sliding window validation is carried out with the following parameters:
training window width: 5, training window step: 1, test window width: 5, horizon: 1. The
meaning of the horizon here means that what will be predicted is 1 period in the future (1
month ahead).
The algorithm method used is neural network, neural network is applied to the model, and
its performance is calculated by forecasting performance elements. The process of predictive
modeling is shown in the figure below
Figure 4. Revenue Prediction Model
9. Predictive Business Intelligence: Consumer Goods Sales Forecasting Using Artificial Neural Network
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The results of the modeling are as follows:
Figure 5. Revenue Prediction Model Performance
From the picture above it was concluded, the prediction results from the previous 6
months to predict the next 1 month resulted in an average accuracy of 0.718 (71.8%). The
revenue predictions that have been made will be plotted so that the trend movement can be
seen whether follow the actual data or not. The figure below is a plot between actual revenue
and revenue prediction. Actual Revenue is shown by a red line; Revenue Prediction is
indicated by a blue line.
Figure 6. Revenue Prediction vs Actual Revenue Trend line
It is expected that after the report is formed using Business Intelligence, stakeholders can
easily capture information through a friendlier visualization than using a conventional system,
Excel, with visualization based on existing data that can provide insight and be able to be
taken into consideration for decision making based on data. With the support of reporting
made with Business Intelligence reliable reports will be generated that can be analyzed by
company leaders so that decision making becomes faster and more effective. The revenue
prediction feature of the new system design can be used by companies to take preventive
actions or better campaign plans to produce better turnover for the company. With the
construction of a data warehouse system along with revenue predictions, it is proven that it
10. Yulyardo and Sani M. Isa
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can make decision support systems and reports faster, more precise, accurate and easier for
users.
5. CONCLUSION
From the research conducted company should do some approaches, such as data analysis,
design data warehouse, and then implement Business Intelligence to make reports become
easier. The reports can help stakeholders to know the progress, to make decision and strategy,
and to evaluate the sales performance. By using Qlik Sense BI Tools and Predictive Data
Mining using Rapidminer Tools, managers can see the revenue distribution map, sales
performance per area per period, and sales dashboard include top 20 best-selling product, top
10 best performing salesman, and etc. The report of revenue distribution map can help
managers to know which branch conform the target and to analyze which branch needs
attention to increase performance. The sales performance report shows the performance of
each sales so that managers can evaluate their job. And last, sales dashboard can help
managers to see the best performance. Overall, this reports can help company to companies to
take preventive actions or better campaign plans to produce better turnover for the company.
With the construction of a data warehouse system along with revenue predictions, it is proven
that it can make decision support systems and reports faster, more precise, accurate and easier
for users.
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