A study model on the impact of various indicators in the performance of stude...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Due to the increasing interest in big data especially in the educational field and online education has led to a conflict in terms of performance indicators of the student. In this paper we discuss the methodology of assessing the student performance in terms of the success indicators revealing a number of indicators that is recommended to indicate success of the final academic achievement.
Due to the increasing interest in big data especially in the educational field and online education has led to a conflict in terms of performance indicators of the student. In this paper we discuss the methodology of assessing the student performance in terms of the success indicators revealing a number of indicators that is recommended to indicate success of the final academic achievement
This proposed system will help in consulting the career opportunities to the students after 10th, 12th or graduation for their bright future and will show the recent industrial trends in that particular profession. In this system we will be working on real time web-based application which will provide students forum for discussion, real time job updates from industry, different industrial events nearby places, live chat with the professional experts. User can apply for the jobs. Database management, real time system and web-based languages will be used design this application. This proposed system will provide the direct communication platform for students with the industry. This system will help the students or employees to build the professional career, resume according to the format approved by industry. User can update and share their documents and experiences with the industry. This system will provide automated verification system with the help of network security. Priyanka Bodke | Nikita Kale | Sneha Jha | Vaishnavi Joshi"Real Time Application for Career Guidance" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-3 , April 2018, URL: http://www.ijtsrd.com/papers/ijtsrd11525.pdf http://www.ijtsrd.com/engineering/computer-engineering/11525/real-time-application-for-career-guidance/priyanka-bodke
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
Higher education institutions now a days are operating in an increasingly complex and
competitive environment. The application of innovation is a must for sustaining its competitive advantage.
Institution leaders are using data management and analytics to question the status quo and develop effective
solutions. Achieving these insights and information requires not a single report from a single system, but
rather the ability to access, share, and explore institution-wide data that can be transformed into meaningful
insights at every level of the institution. Consequently, institutions are facing problems in providing necessary
information technology support for fulfilling excellence in performance. More specifically, the best practices
of big data management and analytics need to be considered within higher education institutions. Therefore,
the study aimed at investigating big data and analytics, in terms of: (1) definition; (2) its most important
principles; (3) models; and (4) benefits of its use to fulfill performance excellence in higher education
institutions. This involves shedding light on big data and analytics models and the possibility of its use in
higher education institutions, and exploring the effect of using big data and analytics in achieving performance
excellence. To reach these objectives, the researcher employed a qualitative research methodology for
collecting and analyzing data. The study concluded the most important result, that there is a significant
relationship between big data and analytics and excellence of performance as big data management and
analytics mainly aims at achieving tasks quickly with the least effort and cost. These positive results support
the use of big data and analytics in institutions and improving knowledge in this field and providing a practical
guide adaptable to the institution structure. This paper also identifies the role of big data and analytics in
institutions of higher education worldwide and outlines the implementation challenges and opportunities in the
education industry.
A study model on the impact of various indicators in the performance of stude...eSAT Publishing House
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology
Due to the increasing interest in big data especially in the educational field and online education has led to a conflict in terms of performance indicators of the student. In this paper we discuss the methodology of assessing the student performance in terms of the success indicators revealing a number of indicators that is recommended to indicate success of the final academic achievement.
Due to the increasing interest in big data especially in the educational field and online education has led to a conflict in terms of performance indicators of the student. In this paper we discuss the methodology of assessing the student performance in terms of the success indicators revealing a number of indicators that is recommended to indicate success of the final academic achievement
This proposed system will help in consulting the career opportunities to the students after 10th, 12th or graduation for their bright future and will show the recent industrial trends in that particular profession. In this system we will be working on real time web-based application which will provide students forum for discussion, real time job updates from industry, different industrial events nearby places, live chat with the professional experts. User can apply for the jobs. Database management, real time system and web-based languages will be used design this application. This proposed system will provide the direct communication platform for students with the industry. This system will help the students or employees to build the professional career, resume according to the format approved by industry. User can update and share their documents and experiences with the industry. This system will provide automated verification system with the help of network security. Priyanka Bodke | Nikita Kale | Sneha Jha | Vaishnavi Joshi"Real Time Application for Career Guidance" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-3 , April 2018, URL: http://www.ijtsrd.com/papers/ijtsrd11525.pdf http://www.ijtsrd.com/engineering/computer-engineering/11525/real-time-application-for-career-guidance/priyanka-bodke
International Journal of Engineering Research and Development (IJERD)IJERD Editor
journal publishing, how to publish research paper, Call For research paper, international journal, publishing a paper, IJERD, journal of science and technology, how to get a research paper published, publishing a paper, publishing of journal, publishing of research paper, reserach and review articles, IJERD Journal, How to publish your research paper, publish research paper, open access engineering journal, Engineering journal, Mathemetics journal, Physics journal, Chemistry journal, Computer Engineering, Computer Science journal, how to submit your paper, peer reviw journal, indexed journal, reserach and review articles, engineering journal, www.ijerd.com, research journals,
yahoo journals, bing journals, International Journal of Engineering Research and Development, google journals, hard copy of journal
Higher education institutions now a days are operating in an increasingly complex and
competitive environment. The application of innovation is a must for sustaining its competitive advantage.
Institution leaders are using data management and analytics to question the status quo and develop effective
solutions. Achieving these insights and information requires not a single report from a single system, but
rather the ability to access, share, and explore institution-wide data that can be transformed into meaningful
insights at every level of the institution. Consequently, institutions are facing problems in providing necessary
information technology support for fulfilling excellence in performance. More specifically, the best practices
of big data management and analytics need to be considered within higher education institutions. Therefore,
the study aimed at investigating big data and analytics, in terms of: (1) definition; (2) its most important
principles; (3) models; and (4) benefits of its use to fulfill performance excellence in higher education
institutions. This involves shedding light on big data and analytics models and the possibility of its use in
higher education institutions, and exploring the effect of using big data and analytics in achieving performance
excellence. To reach these objectives, the researcher employed a qualitative research methodology for
collecting and analyzing data. The study concluded the most important result, that there is a significant
relationship between big data and analytics and excellence of performance as big data management and
analytics mainly aims at achieving tasks quickly with the least effort and cost. These positive results support
the use of big data and analytics in institutions and improving knowledge in this field and providing a practical
guide adaptable to the institution structure. This paper also identifies the role of big data and analytics in
institutions of higher education worldwide and outlines the implementation challenges and opportunities in the
education industry.
Information Science Vs. Information Management: An Analytical PerspectiveScientific Review SR
Information is power and great stakeholder of development many ways. Information and Knowledge
consider as prime mover of the society. In knowledge market many subjects are responsible and deals with
information activities. Fundamentally these works are co llection, selection, organization, processing and
management of information and similar facet. Some knowledge related subjects are Information Studies,
Information Management, Information Science, Information Technology, Information Systems, Documentation
and Librarianship. There are many tools are use for managing information. Present paper highlights various
aspects of two leading information management subjects these are Information Science and Information
Management including their similarity and comparison, briefly. Paper also presents a brief on carrier
opportunities in these two domains.
Rule-based expert systems for supporting university studentsertekg
Download Link > https://ertekprojects.com/gurdal-ertek-publications/blog/rule-based-expert-systems-for-supporting-university-students/
There are more than 15 million college students in the US alone. Academic advising for courses and scholarships is typically performed by human advisors, bringing an immense managerial workload to faculty members, as well as other staff at universities. This paper reports and discusses the development of two educational expert systems at a private international university. The first expert system is a course advising system which recommends courses to undergraduate students. The second system suggests scholarships to undergraduate students based on their eligibility. While there have been reported systems for course advising, the literature does not seem to contain any references to expert systems for scholarship recommendation and eligibility checking. Therefore the scholarship recommender that we developed is first of its kind. Both systems have been implemented and tested using Oracle Policy Automation (OPA) software.
WEB-BASED DATA MINING TOOLS : PERFORMING FEEDBACK ANALYSIS AND ASSOCIATION RU...IJDKP
This paper aims to explain the web-enabled tools for educational data mining. The proposed web-based
tool developed using Asp.Net framework and php can be helpful for universities or institutions providing
the students with elective courses as well improving academic activities based on feedback collected from
students. In Asp.Net tool, association rule mining using Apriori algorithm is used whereas in php based
Feedback Analytical Tool, feedback related to faculty and institutional infrastructure is collected from
students and based on that Feedback it shows performance of faculty and institution. Using that data, it
helps management to improve in-house training skills and gains knowledge about educational trends which
is to be followed by faculty to improve the effectiveness of the course and teaching skills.
Companies desires for making productive discoveries from big data have motivated academic institutions offering variety of different data science (DS) programs, in order to increases their graduates' ability to be data scientists who are capable to face the challenges of the new age. These data science programs represent a combination of subject areas from several disciplines. There are few studies have examined data science programs within a particular discipline, such as Business (e.g. Chen et al.). However, there are very few empirical studies that investigate DS programs and explore its curriculum structure across disciplines. Therefore, this study examines data science programs offered by American universities. The study aims to depict the current state of data science education in the U.S. to explore what discipline DS programs covers at the graduate level. The current study conducted an exploratory content analysis of 30 DS programs in the United States from a variety of disciplines. The analysis was conducted on course titles and course descriptions level. The study results indicate that DS programs required varying numbers of credit hours, including practicum and capstone. Management schools seem to take the lead and the initiative in lunching and hosting DS programs. In addition, all DS programs requires the basic knowledge of database design, representation, extraction and management. Furthermore, DS programs delivered information skills through their core courses. Moreover, the study results show that almost 40 percent of required courses in DS programs is involved information representations, retrieval and programming. Additionally, DS programs required courses also addressed communication visualization and mathematics skills.
A Review of Big Data Analytics in Sector of Higher EducationIJERA Editor
This paper is about the use of big data analytics in higher education. In this paper, we see what the big data is and where does it come from. We will also try to find why the big data analytics has become a buzzword in almost every sector today through our literature review on the big data analytics and its applications in higher education sector. Then we see what the big educational data is, how it is generated and analyzed. We found that the two most important types of analytics are- Learning and academic analytics which will be discussed. Several papers describe the benefits of implementation of analytics in the education sector and the opportunities provided which will be discussed in this paper. We also found that the basic characteristics such as size, speed, variety and some other factors are responsible for some issues and challenges to the use of analytics in this sector. We will discuss those issues and challenges and discuss some proposed solutions to address them.
Industrial Benchmarking through Information Visualization and Data Envelopmen...ertekg
Download Link > https://ertekprojects.com/gurdal-ertek-publications/blog/industrial-benchmarking-through-information-visualization-and-data-envelopment-analysis-a-new-framework/
We present a benchmarking study on the companies in the Turkish food industry based on their financial data. Our aim is to develop a comprehensive benchmarking framework using Data Envelopment Analysis (DEA) and information visualization. Besides DEA, a traditional tool for financial benchmarking based on financial ratios is also incorporated. The consistency/inconsistency between the two methodologies is investigated using information visualization tools. In addition, k-means clustering, a fundamental method from machine learning, is applied to understand the relationship between k-means clustering and DEA.
Competitiveness of Top 100 U.S. Universities: A Benchmark Study Using Data En...ertekg
Download Link > https://ertekprojects.com/gurdal-ertek-publications/blog/benchmark-study-using-data-envelopment-analysis/
This study presents a comprehensive benchmarking study of the top 100 U.S. Universities. The methodologies used to come up with insights into the domain are Data Envelopment Analysis (DEA) and information visualization. Various approaches to evaluating academic institutions have appeared in the literature, including a DEA literature dealing with the ranking of universities. Our study contributes to this literature by the extensive incorporation of information visualization and subsequently the discovery of new insights.
World University Rankings 2014-2015 methodology
Underpinning the World University Rankings 2014-2015 is a sophisticated exercise in information-gathering and analysis: here we detail the criteria used to assess the global academy's greatest universities
The Times Higher Education World University Rankings are the only global university performance tables to judge research-led universities across all their core missions - teaching, research, knowledge transfer and international outlook.
We employ 13 carefully calibrated performance indicators to provide the most comprehensive and balanced comparisons, which are trusted by students, academics, university leaders, industry and governments.
The methodology for the 2014-2015 World University Rankings is identical to that used since 2011-2012, offering a year-on-year comparison based on true performance rather than methodological change.
Online payment portals are a powerful tool that makes our life simple and gives the luxury to make all required payment transactions around any part of the World. The advancement of internet and logistics systems, now it is possible for anybody to shop any product around the world and get it shipped to his\her. The main objectives are to study the problems faced through the online payment system. To study the factors influencing the online payment system.
Readiness measurement of IT implementation in Higher Education Institutions i...TELKOMNIKA JOURNAL
This article elaborates the result of the Pilot Study which is related to IT implementation factors at the Higher Education Institution (HEI), a pilot study is used to validate quantitative readiness model of IT implementation. The main objective of this study is examining the factors that influence the readiness of IT implementation in HEI. This study attempts to analyze IT Content factors, Institutional Context, People, Process, Technology, Service Quality and IT Implementation Readiness (ITIR). The sample of data was taken from 150 HEIs throughout Indonesia which was then processed in statistical techniques through PLS-SEM method. The research finding shows that 9 of the 14 hypotheses used as ITIR model construct have a very significant influence on IT implementation on HEI, so that this finding can provide a comprehensive contribution to the literature of ITIR model development.
Evaluation of the E Government Quality of Services Case Study X City Governmentijtsrd
The application of Information Technology in government is not only based on the desire to create a more efficient government, but also to improve the public access to information and the quality of services developed by the government. This study measures the extent of the quality of citizens' aspirations service at Badung Communication and Information website. The method used is the E Govqual method, since it was created specifically to assess government owned websites. E Govqual itself has 22 attributes which are divided into five variables namely Ease of Use, Trust, Reliability, Content and Appearance of Information, and Citizen Support. The data collected were analyzed using the Importance Performance Analysis IPA method in order to obtain indicators that are in need of improvement or to be maintained based on users perceptions and expectations. The result of the analysis shows that the citizens' aspirations service at Badung Communication and Information website is still not in accordance to the users expectations. This is shown by the suitability value of 100 , which is 81 and the average result of the gap value of 0, which is 0.84. There are 10 attributes of the main improvements to the citizens' aspirations service at Badung Communication and Information website. Dela Handayani | I Ketut Adi Purnawan | Gusti Made Arya Sasmita "Evaluation of the E-Government Quality of Services (Case Study: X City Government)" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-4 , June 2020, URL: https://www.ijtsrd.com/papers/ijtsrd30854.pdf Paper Url :https://www.ijtsrd.com/engineering/information-technology/30854/evaluation-of-the-egovernment-quality-of-services-case-study-x-city-government/dela-handayani
This paper introduces the competency models for Operations Manager, User Interface
Designer, and Application Developers. It will serve as a guide for Information Systems students
to identify which among the three of the offered tracks would be most suited for them to pursue
according to their knowledge, skills, values and interests. The Holland’s RIASEC model and the
Values Search model of Bronwyn and Holt were utilized to determine the most dominant interest
and most dominant values of the industry computing experts. Survey assessment forms were sent
to IT Operations Manager, User Interface Designer, and Application Developer. Most dominant
values and interests of industry computing experts were determined as well as the knowledge
and skills which are mostly required by the industry in their particular area. Based on the result
of the survey, it shows that application developer and user interface designer have a closely
related values. Thus a second round of a survey would be needed to come up with the most
exclusive dominant values for the particular information systems specialization track.
Information Science Vs. Information Management: An Analytical PerspectiveScientific Review SR
Information is power and great stakeholder of development many ways. Information and Knowledge
consider as prime mover of the society. In knowledge market many subjects are responsible and deals with
information activities. Fundamentally these works are co llection, selection, organization, processing and
management of information and similar facet. Some knowledge related subjects are Information Studies,
Information Management, Information Science, Information Technology, Information Systems, Documentation
and Librarianship. There are many tools are use for managing information. Present paper highlights various
aspects of two leading information management subjects these are Information Science and Information
Management including their similarity and comparison, briefly. Paper also presents a brief on carrier
opportunities in these two domains.
Rule-based expert systems for supporting university studentsertekg
Download Link > https://ertekprojects.com/gurdal-ertek-publications/blog/rule-based-expert-systems-for-supporting-university-students/
There are more than 15 million college students in the US alone. Academic advising for courses and scholarships is typically performed by human advisors, bringing an immense managerial workload to faculty members, as well as other staff at universities. This paper reports and discusses the development of two educational expert systems at a private international university. The first expert system is a course advising system which recommends courses to undergraduate students. The second system suggests scholarships to undergraduate students based on their eligibility. While there have been reported systems for course advising, the literature does not seem to contain any references to expert systems for scholarship recommendation and eligibility checking. Therefore the scholarship recommender that we developed is first of its kind. Both systems have been implemented and tested using Oracle Policy Automation (OPA) software.
WEB-BASED DATA MINING TOOLS : PERFORMING FEEDBACK ANALYSIS AND ASSOCIATION RU...IJDKP
This paper aims to explain the web-enabled tools for educational data mining. The proposed web-based
tool developed using Asp.Net framework and php can be helpful for universities or institutions providing
the students with elective courses as well improving academic activities based on feedback collected from
students. In Asp.Net tool, association rule mining using Apriori algorithm is used whereas in php based
Feedback Analytical Tool, feedback related to faculty and institutional infrastructure is collected from
students and based on that Feedback it shows performance of faculty and institution. Using that data, it
helps management to improve in-house training skills and gains knowledge about educational trends which
is to be followed by faculty to improve the effectiveness of the course and teaching skills.
Companies desires for making productive discoveries from big data have motivated academic institutions offering variety of different data science (DS) programs, in order to increases their graduates' ability to be data scientists who are capable to face the challenges of the new age. These data science programs represent a combination of subject areas from several disciplines. There are few studies have examined data science programs within a particular discipline, such as Business (e.g. Chen et al.). However, there are very few empirical studies that investigate DS programs and explore its curriculum structure across disciplines. Therefore, this study examines data science programs offered by American universities. The study aims to depict the current state of data science education in the U.S. to explore what discipline DS programs covers at the graduate level. The current study conducted an exploratory content analysis of 30 DS programs in the United States from a variety of disciplines. The analysis was conducted on course titles and course descriptions level. The study results indicate that DS programs required varying numbers of credit hours, including practicum and capstone. Management schools seem to take the lead and the initiative in lunching and hosting DS programs. In addition, all DS programs requires the basic knowledge of database design, representation, extraction and management. Furthermore, DS programs delivered information skills through their core courses. Moreover, the study results show that almost 40 percent of required courses in DS programs is involved information representations, retrieval and programming. Additionally, DS programs required courses also addressed communication visualization and mathematics skills.
A Review of Big Data Analytics in Sector of Higher EducationIJERA Editor
This paper is about the use of big data analytics in higher education. In this paper, we see what the big data is and where does it come from. We will also try to find why the big data analytics has become a buzzword in almost every sector today through our literature review on the big data analytics and its applications in higher education sector. Then we see what the big educational data is, how it is generated and analyzed. We found that the two most important types of analytics are- Learning and academic analytics which will be discussed. Several papers describe the benefits of implementation of analytics in the education sector and the opportunities provided which will be discussed in this paper. We also found that the basic characteristics such as size, speed, variety and some other factors are responsible for some issues and challenges to the use of analytics in this sector. We will discuss those issues and challenges and discuss some proposed solutions to address them.
Industrial Benchmarking through Information Visualization and Data Envelopmen...ertekg
Download Link > https://ertekprojects.com/gurdal-ertek-publications/blog/industrial-benchmarking-through-information-visualization-and-data-envelopment-analysis-a-new-framework/
We present a benchmarking study on the companies in the Turkish food industry based on their financial data. Our aim is to develop a comprehensive benchmarking framework using Data Envelopment Analysis (DEA) and information visualization. Besides DEA, a traditional tool for financial benchmarking based on financial ratios is also incorporated. The consistency/inconsistency between the two methodologies is investigated using information visualization tools. In addition, k-means clustering, a fundamental method from machine learning, is applied to understand the relationship between k-means clustering and DEA.
Competitiveness of Top 100 U.S. Universities: A Benchmark Study Using Data En...ertekg
Download Link > https://ertekprojects.com/gurdal-ertek-publications/blog/benchmark-study-using-data-envelopment-analysis/
This study presents a comprehensive benchmarking study of the top 100 U.S. Universities. The methodologies used to come up with insights into the domain are Data Envelopment Analysis (DEA) and information visualization. Various approaches to evaluating academic institutions have appeared in the literature, including a DEA literature dealing with the ranking of universities. Our study contributes to this literature by the extensive incorporation of information visualization and subsequently the discovery of new insights.
World University Rankings 2014-2015 methodology
Underpinning the World University Rankings 2014-2015 is a sophisticated exercise in information-gathering and analysis: here we detail the criteria used to assess the global academy's greatest universities
The Times Higher Education World University Rankings are the only global university performance tables to judge research-led universities across all their core missions - teaching, research, knowledge transfer and international outlook.
We employ 13 carefully calibrated performance indicators to provide the most comprehensive and balanced comparisons, which are trusted by students, academics, university leaders, industry and governments.
The methodology for the 2014-2015 World University Rankings is identical to that used since 2011-2012, offering a year-on-year comparison based on true performance rather than methodological change.
Online payment portals are a powerful tool that makes our life simple and gives the luxury to make all required payment transactions around any part of the World. The advancement of internet and logistics systems, now it is possible for anybody to shop any product around the world and get it shipped to his\her. The main objectives are to study the problems faced through the online payment system. To study the factors influencing the online payment system.
Readiness measurement of IT implementation in Higher Education Institutions i...TELKOMNIKA JOURNAL
This article elaborates the result of the Pilot Study which is related to IT implementation factors at the Higher Education Institution (HEI), a pilot study is used to validate quantitative readiness model of IT implementation. The main objective of this study is examining the factors that influence the readiness of IT implementation in HEI. This study attempts to analyze IT Content factors, Institutional Context, People, Process, Technology, Service Quality and IT Implementation Readiness (ITIR). The sample of data was taken from 150 HEIs throughout Indonesia which was then processed in statistical techniques through PLS-SEM method. The research finding shows that 9 of the 14 hypotheses used as ITIR model construct have a very significant influence on IT implementation on HEI, so that this finding can provide a comprehensive contribution to the literature of ITIR model development.
Evaluation of the E Government Quality of Services Case Study X City Governmentijtsrd
The application of Information Technology in government is not only based on the desire to create a more efficient government, but also to improve the public access to information and the quality of services developed by the government. This study measures the extent of the quality of citizens' aspirations service at Badung Communication and Information website. The method used is the E Govqual method, since it was created specifically to assess government owned websites. E Govqual itself has 22 attributes which are divided into five variables namely Ease of Use, Trust, Reliability, Content and Appearance of Information, and Citizen Support. The data collected were analyzed using the Importance Performance Analysis IPA method in order to obtain indicators that are in need of improvement or to be maintained based on users perceptions and expectations. The result of the analysis shows that the citizens' aspirations service at Badung Communication and Information website is still not in accordance to the users expectations. This is shown by the suitability value of 100 , which is 81 and the average result of the gap value of 0, which is 0.84. There are 10 attributes of the main improvements to the citizens' aspirations service at Badung Communication and Information website. Dela Handayani | I Ketut Adi Purnawan | Gusti Made Arya Sasmita "Evaluation of the E-Government Quality of Services (Case Study: X City Government)" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-4 , June 2020, URL: https://www.ijtsrd.com/papers/ijtsrd30854.pdf Paper Url :https://www.ijtsrd.com/engineering/information-technology/30854/evaluation-of-the-egovernment-quality-of-services-case-study-x-city-government/dela-handayani
This paper introduces the competency models for Operations Manager, User Interface
Designer, and Application Developers. It will serve as a guide for Information Systems students
to identify which among the three of the offered tracks would be most suited for them to pursue
according to their knowledge, skills, values and interests. The Holland’s RIASEC model and the
Values Search model of Bronwyn and Holt were utilized to determine the most dominant interest
and most dominant values of the industry computing experts. Survey assessment forms were sent
to IT Operations Manager, User Interface Designer, and Application Developer. Most dominant
values and interests of industry computing experts were determined as well as the knowledge
and skills which are mostly required by the industry in their particular area. Based on the result
of the survey, it shows that application developer and user interface designer have a closely
related values. Thus a second round of a survey would be needed to come up with the most
exclusive dominant values for the particular information systems specialization track.
An Empirical Study of the Applications of Classification Techniques in Studen...IJERA Editor
University servers and databases store a huge amount of data including personal details, registration details, evaluation assessment, performance profiles, and many more for students and lecturers alike. main problem that faces any system administration or any users is data increasing per-second, which is stored in different type and format in the servers, learning about students from a huge amount of data including personal details, registration details, evaluation assessment, performance profiles, and many more for students and lecturers alike. Graduation and academic information in the future and maintaining structure and content of the courses according to their previous results become importance. The paper objectives are extract knowledge from incomplete data structure and what the suitable method or technique of data mining to extract knowledge from a huge amount of data about students to help the administration using technology to make a quick decision. Data mining aims to discover useful information or knowledge by using one of data mining techniques, this paper used classification technique to discover knowledge from student’s server database, where all students’ information were registered and stored. The classification task is used, the classifier tree C4.5, to predict the final academic results, grades, of students. We use classifier tree C4.5 as the method to classify the grades for the students .The data include four years period [2006-2009]. Experiment results show that classification process succeeded in training set. Thus, the predicted instances is similar to the training set, this proves the suggested classification model. Also the efficiency and effectiveness of C4.5 algorithm in predicting the academic results, grades, classification is very good. The model also can improve the efficiency of the academic results retrieving and evidently promote retrieval precision.
ow-a-days data volumes are growing rapidly in several domains. Many factors have contributed to this growth, including inter alia proliferation of observational devices, miniaturization of various sensors ,improved logging and tracking of systems, and improvements in the quality and capacity of both disk storage and networks .Analyzing such data provides insights that can be used to guide decision making. To be effective, analysis must be timely and cope with data scales. The scale of the data and the rates at which they arrive make manual inspection infeasible. As an educational management tool, predictive analytics can help and improve the quality of education by letting decision makers address critical issues such as enrollment management and curriculum Development. This paper presents an analytical study of this approach’s prospects for education planning. The goals of predictive analytics are to produce relevant information, actionable insight, better outcomes, and smarter decisions, and to predict future events by analyzing the volume, veracity, velocity, variety, value of large amounts of data and interactive exploration.
Selection of Articles using Data Analytics for Behavioral Dissertation Resear...PhD Assistance
Outcomes in health-related issues including psychological, educational, Behavioral, environmental, and social are intended to sustain positive change by digital interferences. These changes may be delivered using any digital device like a phone or computer, and make them gainful for the provider. Complex and large-scale datasets that contain usage data can be yielded by testing a digital intervention. This data provides invaluable detail about how the users interact with these interventions and notify their knowledge of engagement, if they are analyzed properly. This paper recommends an innovative framework for the process of analyzing usage associated with a digital intervention .
PhD Assistance is an Academic The Best Dissertation Writing Service & Consulting Support Company established in 2001. specialiWeze in providing PhD Assignments, PhD Dissertation Writing Help , Statistical Analyses, and Programming Services to students in the USA, UK, Canada, UAE, Australia, New Zealand, Singapore and many more.
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The Architecture of System for Predicting Student Performance based on the Da...Thada Jantakoon
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1. See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/332678212
A Systematic Literature Review of Business Intelligence Technology,
Contribution and Application for Higher Education
Conference Paper · October 2018
DOI: 10.1109/ICITSI.2018.8696019
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3. steps are defining the criteria, defining the resources,
literature selection, data collection, and data item
selection. Some common reason to use this method are to
identify specific domain of research and create a
summary of result. This paper is made with the structure
is introduction, research methodology, research results,
and conclusions.
II. RESEARCH METHODOLOGY
A. Identification
The first is to identify the resource. The journal that
filtered in the identification process is a journal that
obtained from several database journals that are very
commonly used and easily accessible. The database
journal are springer, ScienceDirect, ACM, and IEEE.
The second step is defining the resource by search on
journal database. To define the resource, keyword is
important to limit the topic of the literature. The
keywords used to obtain related publications are
"Business Intelligence" AND ("Higher Education" OR
"Institution" OR "Campus" OR 'University").
B. Screening & Eligibility
Screening and Eligibility done after identifying the
resources and keywords that searched. The next step is
to screen the results obtained. Based on search results
using keywords, there are several relevant articles with
keywords contained in Table I.
TABLE I RESULT OF SEARCH KEYWORD ON JOURNAL
DATABASE
Database Journal Total Article
IEEE 19
ScienceDirect 273
Springer 615
ACM 12
Total 919
The article that obtained was 919 before through
screening. All articles that obtained through a screening
process to eliminate duplication and at the same time
through the eligibility stages. These stages are in
accordance with the criteria to eliminate the articles
contained in Table II. Applying include and exclude in
Table II reduce the number of article.
TABLE N INCLUDING AND EXLUDING CRITERIA
Criteria
Include Article, Journal, Proceeding
The topic is Business Intelligence for Higher
Education
Article in English
Open Access
Exclude Books, Chapter, Thesis, Magazine
White Paper
Abstract, less than 4 pages
C. Included
After going through the elimination process, the
number of articles included in the relevant topic criteria
is 12 articles. Articles from ACM is 100% reduce,
because all of the result is not open access. Springer only
1,3% of records that have related result based on
keyword. After through the process screening on the
topic, none of the articles included. ScienceDirect give
the highest number forrelevant article based on keyword
search. The result of this database journal is 4,76% of
records that relevant and open access. IEEE is give the
exactly same result with Springer. Based on all of the
result, only 1,3% of records are include and we can
conclude that ScienceDirect is easy to access some
related article with the keyword "Business Intelligence"
AND ("Higher Education" OR "Institution" OR
"Campus" OR 'University").
Fig 1. Flow ofInformation
The research methodology that used was to survey
several literatures with the aim of answering the
formulation of research problems. The research question
used to facilitate the process of identifying answers to
the literature and defining the topic. The following is a
list of questions used in the research contained in Table
III.
TABLE PI LIST OF RESEARCH QUESTION
ID Research Question* Purpose
Ql What kind of technique or
technology that support
implementation of Business
Intelligence for higher
education?
To identify the technology for the
implementation of Business
Intelligence for higher education
Q2 What is the contribution of
business intelligence for
higher education?
To identify the contribution of
business intelligence for higher
education
Q3 What kind of application
implementation of business
intelligence for higher
education
To identify variety of application of
business intelligence for higher
education
The answer of the research questions obtained by
reviewing the literature. Based on these criteria, the
number of articles obtained was 20 articles. The third
step is selection of the literature that done by explore the
title, abstract, and keyword of the article. Beside
exploration, partial reading also used to eliminate the
article. The fourth step is more detail than the third step
that read partial the article. This step is collected the data
after partial reading and create the data extraction form.
After selection, the next step is to identify the
answers to the research questions in each article that
selected. The answer of research question contained in
the next section, namely section 3.
405
4. III. RESEARCH RESULT
Business intelligence is a system that manages
business activities starting from marketing, operations,
and various aspects. Not only for business, but also in
the forwarding of organizations and institutions is very
helpful in making decisions. Business intelligence is the
ability of business people whether companies or
organizations to utilize available data and technology. BI
has the role to turn data into information that is useful
for businesses and build a knowledge [8]. The
development of the use of business intelligence enjoyed
from various sectors, including education.
The education sector can also utilize this technology
to optimize functions in the organization. Identification
carried out based on a research question of three
questions. The first question (Ql) aims to identify the
techniques used in implementing intelligence business
for higher education. The second question (Q2) aims to
identify what are the contributions of business
intelligence to higher education. The last one is to
answer the question (Q3) which aims to identify
applications from business intelligence for higher
education.
A. BIfor Higher Education Technology
Technology is one part of the architecture that used
as a reference in building business intelligence to meet
needs. The future of business intelligence requires
several technologies to realize the design. Based on the
results of the review carried out, in general the
technology of applying business intelligence divided
into two. First is the technique used and the second is the
tools or products from technology. The following are the
technologies used in implementing business intelligence
for higher education.
1) Technique: This section summarizes the
techniques used to implement business intelligence on
higher education. Broadly speaking, techniques that
identified from literatures made into five points in
general.
a) Data Mining: Data mining is a semi-
automatic process that analyses large databases into a
pattern [9]. The application of business intelligence to
higher education using technology, one of which is by
supervised learning and multivariate analysis.
Supervised learning techniques are used one of them is
the decision tree to classify data [10], The data in
question is data derived from students.
b) Viable System Model (VSM): This technique
is one of various technique that often used to explore the
complexity of an organization. The application of VSM
to the education sector is one of them is to understand
the case of causation and curriculum development [11].
In addition, VSM also used to assess the framework of
e-Learning and social interaction. This model has five
main functions, including:
• Operational Activity
• Coordination and Service System
• Management Control and Resource Allocation
• Audit
• Intelligence, analysing the internal and internal
trends and evaluating the implications for the
future.
• Policy and Ethos.
c) Learning Analytics: The technique that
analyses this learning process is used by [12] to analyse
the interaction of students with online educational
resources in supporting the learning process. Analysis
done by tracking log records. It used to discover
information on students' mind-set.
d) Cloud Computing: The e-Learning world
needs this technology to improve the quality of
education. Cloud computing technology is also a support
in implementing business intelligence. The large amount
of data causes consideration in dealing with problems in
hardware and software [13]. The use of cloud computing
and big data provides a solution to the collection,
analysis and presenting of data from multiple sources
and types. According to [13], cloud computing can be
used privately or publicly. The choice of using method
based on the need to manage internal data or external
data. Google, IBM, Sun, Amazon, Cisco, Intel, Oracle
are some of the vendors that provide cloud computing.
For the education sector, the type of cloud computing
that recommended is private clouds.
e) Behavioural Analytics: This technology is an
extension of the application of big data and datamining
technology to identify how and why [14], This
technology makes it possible to monitor and detect
anomalies from students with emerging issues.
2) Tools: The tools that used are support for the
application of technology applied to higher education.
Based on the identification results in the literature, the
following are the tools used for the application of
business intelligence.
a) Hadoop: This technology makes it possible to
implement big data technology with cloud environment
systems and support the distribution of big data. Besides
being powerful, this tool is a collaboration of Oracle and
IBM. Hadoop cluster like Yahoo, Facebook provides
contribution and addition value and is quite competitive
with cloud computing technology from Microsoft,
Amazon, and Google.
b) Gephi: A Powerful enough tools to use for
business intelligence application is Gephi. This software
provides facilities to represent data to the form of nodes
and paths. At higher education, this device helps to
describe information related to teachers or students.
c) BigData: Big Data is a technology that allows
to do share data, to analyse, and to build business
intelligence [9]. Based on a review of the relevant paper,
the big data technology that commonly used is oracle's
big data architecture and IBM. Business intelligence
makes the perspective that big data is a technology for
managing large amounts of data from various sources
combined with other technologies [14].
d) Web-Based: One simple technology is to
create web-based applications. Implementation of
business intelligence for higher education is done with a
web application that manages the resources that owned
by institutions [15]. The system built is for decision
support (DSS). This technology not purely used for
406
5. business intelligence. The integration stage or data
staging still requires the role of other devices.
TABLE IV. BI TECHNOLOGY
Type Items Reference Articles
Technique Data Mining [10] [16]
Technique
VSM [11]
Technique
Learning Analytics ri2i
Technique
Cloud Computing [13]
Technique
Behavioural Analytics [14]
Tools Hadoop [17] [18] [19]
Gephi [13]
BigData by IBM T141
Web-Based [15]
B. BIfor Higher Education Contributions
1) Resource Sharing: The exchange of ideas
between teachers and students is the best support for
knowing the knowledge of students.
2) Evolve Knowledge: Progress from students and
the inter-student communication process can accelerate
and improve the process of delivering and understanding
knowledge.
3) Quality Improvement for Managerial Decision:
Quality improvements to managerial decisions imply
services. Not only for institutional business needs, but
also for the needs of students and academic staff.
4) Innovation in Research and Development: An
increase in the development and application of
technology in educational institutions supports higher
education. This contribution derived from the existence
of knowledge transfers that allow institutional members
to make relevant and competitive outputs.
5) The Improvement of Educational Initiative:
Relevant information obtained helps institutional
members to obtain answers to the questions that arise.
Thus, it can support decision making in improving the
quality of education.
6) Prediction of Behaviour: Behaviour analytics
provides an opportunity to identify one's ideology,
behaviour, or thinking. The education sector requires
this system to identify the psychological side of students,
so they can make decisions to deal with problems that
arise.
7) Efficiency and Effectiveness of Resources:
Business intelligence developed to support the decision
making process for executives. It is important to decide
what emerges from executives from a system built from
existing data. Historical data gives executives an idea of
what happened and how to deal with it.
8) The Competitive Improvement: Educational data
used as material to support competitive enhancement
strategies. Competitive learning is the level of quality of
education for students, departments, and institutional
level.
9) The Consumption Trends: Interest in the
institutional environment can be identified, so to provide
an overview of the current trend as a reference for
institutions to improve the quality of education. The
graduates can be able to adjust to the emerging trends.
One way to find out is to know the data contained in
social media.
10) New Model of Assessment: The assessment
system for students developed by utilizing business
intelligence technology. One form of assessment
innovation is to use games without leaving traditional
assessment. This process will be more effective in
providing information from students who assessed.
TABLE V BI Contributions
Contributions Reference Articles
Resource Sharing [14]
Evolve Knowledge [17] [13] [10]
Quality Improvement for Managerial
Decision
[16] [17]
Innovation in Research and Development [14] [19]
The Improvement of Educational Initiative [11]
Prediction of Behaviour [18]
Efficiency and Effectiveness [15]
The Competitive Improvement [19] [22]
The Consumption Trends T201
New Model of Assessment [12]
C. BIfor Higher Education Application
1) Management Resource: One form of application
of BI is to manage resources both human resources,
technology, information, and curriculum. The BI
application can provide a strategy for planning,
budgeting, and allocating resources to higher education
[16]. The implementation of BI for resource
management, one of which is to build a report using tools
that depend on the completeness and integrity of the
system built. The existence of this system provides a
good development of information systems in an
institution [21].
2) Enrolment: BI has potential in the process of
student admission and management. This system will
provide the answers to the questions "what methods and
approaches can applied?" [16]. The selection process
carried out with all considerations to improve quality
and service. Students who are accepted are certainly
those who meet the admission requirements.
Nevertheless, to determine the best method of
acceptance, one of them based on the learning
performance of students who received and input from
students.
3) Postgraduate: Applications to this subject based
on activities in social media to identify skills needed for
postgraduate and trends [20]. The application of BI
developed by using this information to explore
information on graduate activities after completing
studies. Not infrequently on social media found
information from jobs and businesses of graduates.
4) Learning and Curriculum: The application of
business intelligence to support the learning process is
one of them is by managing it using the Learning
Management System or known as eLearning. This
eLearning system consists of a source of information for
courses, modules, or experiments and others made by the
teacher to accelerate the acquisition of knowledge for
students [13].
5) Research: Innovation in research and
development by utilizing business intelligence
technology is one form of application of this technology
in the education sector, namely the field of research.
Structured and unstructured data has the potential
407
6. extracted for the acquisition of relevant information.
This information can also influence findings and
research. One of them is forming new discoveries or
research [19]. The information obtained from a
scientific, a management or a business perspective to
overcome any problems in the organization.
6) Personal: Analysis of behaviour is one form of
expansion of the application of business intelligence
technology, data mining, and big data that focuses on
how and why the behaviour of an individual using data
[18]. Applications in this field are quite complex,
because the behaviour of the student depends on various
factors such as family, friends, habits, and interests.
Some possible data sources used are from institutional
databases that store student information, courses, test
scores. In addition to databases, personal data and web
digital trail used as data sources.
7) Assessment: Assessment is an important aspect
that can determine the success or not of learning
activities carried out [12]. The assessment presented in
the form of a report for the teacher that can be analysed.
The aim is to evaluate and assess how student's progress.
TABLE VIBI APPLICATION
Application Reference Article
Management Resource r i e i r 2 i i r i s i r i 7 i
Enrolment [ 1 6 ]
Postgraduate [ 2 0 ] [ 2 2 ]
Learning and Curriculum [ 1 1 ] [ 1 3 ] [ 1 4 ] [ 1 0 ] [22]
Research [15] [19] [14]
Personal [ 1 8 ]
Assessment [ 1 2 ]
IV. CONCLUSION
Business intelligence technology that manages data
into relevant information can influence the decision
making process. This study raised three aspects that
identified to find out the use of business intelligence for
better education. There are three aspects identified,
namely tools, contributions, and applications. The three
aspects after identified in the related article found and
summarized into important points. Business intelligence
applied to the education sector generally uses data
mining technology as a technology for analysing and
cloud computing as a data storage medium. The
technology requires the help of several devices applied.
Based on identification, the development of business
intelligence generally uses assistance from other parties
such as Hadoop, Gephi, and BigData IBM.
The application of business intelligence not only
used for business, but can also applied to improve the
management process for various fields in the education
sector. Among them are for assessment, behaviour,
research, curriculum and learning, postgraduate, and
resource management. The application can have an
influence on educational institutions in finding
innovations and hidden information that extracted
transferred to those who need the information in
decision-making.
We can see that, along with technological
developments, technology to build business intelligence
solutions will also develop. By building the BI system,
it broadly concluded that it really helps and supports
users in the decision-making process. By going through
several stages that vary from observed research, but in
general it can be seen that the development process of BI
is from the source data integrated into a data warehouse
which can then be carried out by reporting processes by
taking into account the insights that will be obtained
from the system to be built.
Based on the results of the analysis, it can be
concluded that the technology that used to BI application
that widely used is by using data mining. Contribution
from BI to the education sector is not only for
managerial, but can be used to improve human resource
performance and provide insight for innovation in
research. BI applications are generally found to manage
resources, learning, and curriculum. These two things
are found in several paper references obtained through
the prism process, however, there are areas that have the
potential to be further investigated. That is in the
application for research, enrolment, personal, and
assessment that can be used as a research topic for the
future.
V. ACKNOWLEDGMENT
This paper is supported by Faculty of Information
Technology, Andalas University for publication.
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