Employees are the backbone of corporate activities and the giving of bonuses, job titles and allowances to employees to motivate the work of employees is very necessary, salesman on the company very much and to find the best salesman cannot be done manually and for that required the implementation of a system in this decision support system by applying the TOPSIS method, it is expected with the implementation of TOPSIS method the expected results of top management can be fulfilled.
Stages of decision making done by the manager is a crucial stage. Given the resulting decisions affect the sustainability of the organization, then many managers use systems that can support the resulting decisions. This system is known as the decision support system, which applies to solving a problem, using methods such as ELECTRE, Promethee, SAW, TOPSIS. Using decision support systems makes it easy for decision makers to add new data, change data and make decisions more efficiently. In this article, the method used is Technique for Order Preference by Similarity to Ideal Solution (TOPSIS).
This document presents a proposed churn prediction model based on data mining techniques. The model consists of six steps: identifying the problem domain, data selection, investigating the data set, classification, clustering, and utilizing the knowledge gained. The authors apply their model to a data set of 5,000 mobile service customers using data mining tools. They train classification models using decision trees, neural networks, and support vector machines. Customers are classified as churners or non-churners. Churners are then clustered into three groups. The results are interpreted to gain insights into customer retention.
Rank Computation Model for Distribution Product in Fuzzy Multiple Attribute D...TELKOMNIKA JOURNAL
Ranking of an activity is very important to support work effectiveness. Previous works, ranking for distribution product is used by manual process or averaging value. Problem in this research, the research should be found the effective way to rank the distribution product. This research proposes assist the ranking with a computational model based on Fuzzy Multiple Decision Making (FMADM). Getting an effective ranking, a variable in FMADM computing is required. Variables is used in this research such as number of households, number of small-scale enterprises run by households, gross domestic regional income, and economic growth rate of a region. Research completion is assisted by using self-built research methods. Research method consists of determining value of origin, determining degree of membership, determining weight of each variable, calculation of relation matrix, calculation of the preference value in each village for ranking value, and last is sorting. Operationalized FMADM is gain a result with three priorities district. Priority number one is all of district that have a rank or Vij (alternative rank) higher than 0.4. It means only 7% or 5 villages with the highest rank. Priority number second s all of district that have rank between Vij = 0.26 and Vij = 0.4. It means only 62% or 44 villages. Priority number three is district that have a rank lower than Vij = 0.26, and only 31% or 22 villages. Impact in use of FMADM, calculated in rank, is the process runs effective and dynamic with changing of weighted. User can arrange of weighted as needed.
Applying Classification Technique using DID3 Algorithm to improve Decision Su...IJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
International Journal of Modern Engineering Research (IJMER) covers all the fields of engineering and science: Electrical Engineering, Mechanical Engineering, Civil Engineering, Chemical Engineering, Computer Engineering, Agricultural Engineering, Aerospace Engineering, Thermodynamics, Structural Engineering, Control Engineering, Robotics, Mechatronics, Fluid Mechanics, Nanotechnology, Simulators, Web-based Learning, Remote Laboratories, Engineering Design Methods, Education Research, Students' Satisfaction and Motivation, Global Projects, and Assessment…. And many more.
Decision Support System Implementation for Candidate Selection of the Head of...IJRESJOURNAL
ABSTRACT: One of agency under the subdivision of The Indonesian National Army is Bintaldam V Brawijaya, acts as the mental founding agency. The head of affairs position replacement is often occurred in this agency, but the positions currently have a large number of incompetence person in charge. Subjection inthe election process leads to the inaccurate placement, resulting in poor leadership. The process of head of affairs assignment starts from candidates dispatching from each head of administrative section. Those candidates must then meet the three elements of assessment, i.e. the personality element, qualification element, and potential element. The candidates will be selected by head of agency as the top leader in the agency. The head of agency, however, poses difficulties to determine which candidate to put into position, frequently because of no proportional system exists to provide assistance in decision making process. A method is needed tomake more accurate placement for better leadership result.This research utilizegroup technology as the assessment elements hierarchical data structure and decision table as the rule evaluation engine to form a decision support system for making the replacement process of the heads of affairs easier and more accurate.
Harmonized scheme for data mining technique to progress decision support syst...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.
1. The document discusses decision tree analysis as an effective decision-making tool. It describes the key components of a decision tree, including nodes, branches, probability estimates, and payoffs.
2. Decision trees can be used to portray interrelated, sequential, and multi-dimensional decision problems. They help visualize complex problems and identify critical elements.
3. The document provides an example of a simple decision tree involving choices between sowing different types of seeds and the potential outcomes.
This document discusses using an adaptive boosted support vector machine to classify potential direct marketing consumers using bank customer data. It compares the performance of an ordinary SVM classifier to an SVM classifier combined with an Adaboost algorithm. The Adaboost-SVM approach achieved higher accuracy (95.07%) and sensitivity (91.65%) compared to the ordinary SVM (91.67% accuracy and 83.80% sensitivity) in predicting customer subscription prospects from a dataset of over 9,000 records with 20 attributes. The results showed that ensemble methods like Adaboost can improve the performance of a single SVM classifier.
Stages of decision making done by the manager is a crucial stage. Given the resulting decisions affect the sustainability of the organization, then many managers use systems that can support the resulting decisions. This system is known as the decision support system, which applies to solving a problem, using methods such as ELECTRE, Promethee, SAW, TOPSIS. Using decision support systems makes it easy for decision makers to add new data, change data and make decisions more efficiently. In this article, the method used is Technique for Order Preference by Similarity to Ideal Solution (TOPSIS).
This document presents a proposed churn prediction model based on data mining techniques. The model consists of six steps: identifying the problem domain, data selection, investigating the data set, classification, clustering, and utilizing the knowledge gained. The authors apply their model to a data set of 5,000 mobile service customers using data mining tools. They train classification models using decision trees, neural networks, and support vector machines. Customers are classified as churners or non-churners. Churners are then clustered into three groups. The results are interpreted to gain insights into customer retention.
Rank Computation Model for Distribution Product in Fuzzy Multiple Attribute D...TELKOMNIKA JOURNAL
Ranking of an activity is very important to support work effectiveness. Previous works, ranking for distribution product is used by manual process or averaging value. Problem in this research, the research should be found the effective way to rank the distribution product. This research proposes assist the ranking with a computational model based on Fuzzy Multiple Decision Making (FMADM). Getting an effective ranking, a variable in FMADM computing is required. Variables is used in this research such as number of households, number of small-scale enterprises run by households, gross domestic regional income, and economic growth rate of a region. Research completion is assisted by using self-built research methods. Research method consists of determining value of origin, determining degree of membership, determining weight of each variable, calculation of relation matrix, calculation of the preference value in each village for ranking value, and last is sorting. Operationalized FMADM is gain a result with three priorities district. Priority number one is all of district that have a rank or Vij (alternative rank) higher than 0.4. It means only 7% or 5 villages with the highest rank. Priority number second s all of district that have rank between Vij = 0.26 and Vij = 0.4. It means only 62% or 44 villages. Priority number three is district that have a rank lower than Vij = 0.26, and only 31% or 22 villages. Impact in use of FMADM, calculated in rank, is the process runs effective and dynamic with changing of weighted. User can arrange of weighted as needed.
Applying Classification Technique using DID3 Algorithm to improve Decision Su...IJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
International Journal of Modern Engineering Research (IJMER) covers all the fields of engineering and science: Electrical Engineering, Mechanical Engineering, Civil Engineering, Chemical Engineering, Computer Engineering, Agricultural Engineering, Aerospace Engineering, Thermodynamics, Structural Engineering, Control Engineering, Robotics, Mechatronics, Fluid Mechanics, Nanotechnology, Simulators, Web-based Learning, Remote Laboratories, Engineering Design Methods, Education Research, Students' Satisfaction and Motivation, Global Projects, and Assessment…. And many more.
Decision Support System Implementation for Candidate Selection of the Head of...IJRESJOURNAL
ABSTRACT: One of agency under the subdivision of The Indonesian National Army is Bintaldam V Brawijaya, acts as the mental founding agency. The head of affairs position replacement is often occurred in this agency, but the positions currently have a large number of incompetence person in charge. Subjection inthe election process leads to the inaccurate placement, resulting in poor leadership. The process of head of affairs assignment starts from candidates dispatching from each head of administrative section. Those candidates must then meet the three elements of assessment, i.e. the personality element, qualification element, and potential element. The candidates will be selected by head of agency as the top leader in the agency. The head of agency, however, poses difficulties to determine which candidate to put into position, frequently because of no proportional system exists to provide assistance in decision making process. A method is needed tomake more accurate placement for better leadership result.This research utilizegroup technology as the assessment elements hierarchical data structure and decision table as the rule evaluation engine to form a decision support system for making the replacement process of the heads of affairs easier and more accurate.
Harmonized scheme for data mining technique to progress decision support syst...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.
1. The document discusses decision tree analysis as an effective decision-making tool. It describes the key components of a decision tree, including nodes, branches, probability estimates, and payoffs.
2. Decision trees can be used to portray interrelated, sequential, and multi-dimensional decision problems. They help visualize complex problems and identify critical elements.
3. The document provides an example of a simple decision tree involving choices between sowing different types of seeds and the potential outcomes.
This document discusses using an adaptive boosted support vector machine to classify potential direct marketing consumers using bank customer data. It compares the performance of an ordinary SVM classifier to an SVM classifier combined with an Adaboost algorithm. The Adaboost-SVM approach achieved higher accuracy (95.07%) and sensitivity (91.65%) compared to the ordinary SVM (91.67% accuracy and 83.80% sensitivity) in predicting customer subscription prospects from a dataset of over 9,000 records with 20 attributes. The results showed that ensemble methods like Adaboost can improve the performance of a single SVM classifier.
This document presents a new algorithm called UDT-CDF for building decision trees to classify uncertain numerical data. It improves on previous algorithms like UDT that were based on probability density functions (PDFs). The key aspects of the new algorithm are:
1. It uses cumulative distribution functions (CDFs) rather than PDFs to represent uncertain numerical attributes, since CDFs provide more complete probability information.
2. It splits data at decision tree nodes based on the CDF, placing data with values covering the split point into both branches weighted by the CDF.
3. Experimental results show the new CDF-based algorithm achieves more accurate classifications and is more computationally efficient than the PDF-based UDT algorithm,
The Ordered Weighted Averaging (OWA) operator was introduced by Yager [57] to provide a method for aggregating inputs that lie between the max and min operators. In this article two variants of probabilistic extensions the OWA operator-POWA and FPOWA (introduced by Merigo [26] and [27]) are considered as a basis of our generalizations in the environment of fuzzy uncertainty (parts II and III of this work), where different monotone measures (fuzzy measure) are used as uncertainty measures instead of the probability measure. For the identification of “classic” OWA and new operators (presented in parts II and III) of aggregations, the Information Structure is introduced where the incomplete available information in the general decision-making system is presented as a condensation of uncertainty measure, imprecision variable and objective function of weights.
LOAD DISTRIBUTION COMPOSITE DESIGN PATTERN FOR GENETIC ALGORITHM-BASED AUTONO...ijsc
Current autonomic computing systems are ad hoc solutions that are designed and implemented from the
scratch. When designing software, in most cases two or more patterns are to be composed to solve a bigger
problem. A composite design patterns shows a synergy that makes the composition more than just the sum
of its parts which leads to ready-made software architectures. As far as we know, there are no studies on
composition of design patterns for autonomic computing domain. In this paper we propose pattern-oriented
software architecture for self-optimization in autonomic computing system using design patterns
composition and multi objective evolutionary algorithms that software designers and/or programmers can
exploit to drive their work. Main objective of the system is to reduce the load in the server by distributing
the population to clients. We used Case Based Reasoning, Database Access, and Master Slave design
patterns. We evaluate the effectiveness of our architecture with and without design patterns compositions.
The use of composite design patterns in the architecture and quantitative measurements are presented. A
simple UML class diagram is used to describe the architecture.
International Journal of Computational Engineering Research(IJCER)ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
This technical paper discusses using a 2x2 Cartesian matrix framework to aid structured decision making in project management. The framework involves identifying decision areas, analyzing them to determine attributes, then designing a 2x2 matrix with the attributes on the axes to categorize scenarios into four quadrants. Each quadrant represents a unique decision making scenario requiring an identified action. The paper provides examples of decision matrices for stakeholder management, benefit realization, and governance. It also presents a case study where a company used the framework to help achieve the technology modernization project vision of lower ownership costs through consolidating technology.
Business Bankruptcy Prediction Based on Survival Analysis Approachijcsit
This document discusses business bankruptcy prediction models using survival analysis. It analyzes companies listed on the Taiwan Stock Exchange from 2003 to 2009. The study uses the Cox proportional hazards model to identify key financial ratios that predict business failure. The model includes profitability, leverage, efficiency, and valuation ratios as predictors. The accuracy of the proposed survival analysis model in classifying business failures is 87.93%. The document also discusses other statistical and machine learning techniques used for business bankruptcy prediction, such as logistic regression, neural networks, and hybrid models.
Semantic approach utilizing data mining and case based reasoning for it suppo...eSAT Journals
Abstract Information Technology (IT) plays a very important role in all organizations. IT executives are constantly faced with problems that are difficult to tackle. Failure in IT service can interrupt the functioning of an organization. Case-Based Reasoning (CBR) is a problem solving methodology where experience in the form of past cases can be used to solve problems, thereby assisting the automation of problem solving and experience management. Furthermore, the performance, quality and efficiency of CBR systems can be enhanced through data mining. In order to support the IT team for faster and efficient problem resolution, a case-based reasoning approach integrated with data mining techniques could be utilized. In this paper, the study done on various CBR systems and data mining techniques for problem and experience management is explained. A system is proposed for IT experience and problem management with semantic retrieval in order to increase the efficiency and quality of the IT support service. Keywords: Case-based reasoning, Data Mining, Experience management, IT problem management, IT support.
Semantic approach utilizing data mining and case based reasoning for it suppo...eSAT Publishing House
This document discusses using a semantic approach combining data mining and case-based reasoning to improve IT support services. It proposes a system that uses web crawlers to extract IT problem/solution data from public resources. The data is preprocessed and latent semantic analysis is applied to represent the data semantically in lower dimensions. This allows IT teams to semantically retrieve relevant problem/solution cases from the knowledge base to resolve new issues. The system aims to dynamically increase the IT experience knowledge base and guarantee accurate and efficient case retrieval to enhance IT support service quality and efficiency.
IRJET - An Overview of Machine Learning Algorithms for Data ScienceIRJET Journal
This document provides an overview of machine learning algorithms that are commonly used for data science. It discusses both supervised and unsupervised algorithms. For supervised algorithms, it describes decision trees, k-nearest neighbors, and linear regression. Decision trees create a hierarchical structure to classify data, k-nearest neighbors classifies new data based on similarity to existing data, and linear regression finds a linear relationship between variables. Unsupervised algorithms like clustering are also briefly mentioned. The document aims to familiarize data science enthusiasts with basic machine learning techniques.
Human Resource Recruitment using Fuzzy Decision Making MethodIJSRD
Traditional way of recruiting personnel was through a group decision making problem under multiple criteria containing subjectivity, imprecision and vagueness. In order to keep up with increasing competition of globalization and fast technological improvements and changes, Human resource field needs the best fit employee for a job vacancy. This paper proposes a Fuzzy Decision Making (FDM) method for recruitment process of Human Resource management, which is based on the Fuzzy set theory. Different criteria of human resource recruitment process will be given fuzzy linguistic terms such as absolutely low, extremely low, very low, low, medium, high, very high, extremely high, absolutely high depends upon the importance given by the Human Resource manager. Fuzzy Scaled Weight (FSW) will be calculated for all the criteria. Cumulative Fuzzy Value (CFV) is calculated for all the applicants from Fuzzy Scaled Weight values. Interview Fuzzy Value (IFV) is given by the human resource manager for all the applicants attending interviews. Final Fuzzy Value (FFV) will be calculated aggregating both Cumulative Fuzzy Value and Interview Fuzzy Value. Finally, all the applicant records are arranged in the order of FFV values. Then, Human resource manager can select the applicants easily from the arranged list. Fuzzy Decision Making method system is developed to illustrate the above FDM method for the Human Resource recruitment process.
The document discusses decision support systems (DSS), which are computer-based tools that help decision-makers in organizations solve problems and make decisions. It describes the four stages of decision making - intelligence, design, choice, and implementation. It then explains different types of DSS, including communication-based, data-based, document-based, knowledge-based, and model-based systems. Finally, it discusses benefits of using DSS and group decision support systems.
This document provides a tutorial for using the SuperDecisions software to build decision models using the Analytic Hierarchy Process (AHP) or Analytic Network Process (ANP). It explains the basic concepts of clusters and elements, and how to create a hierarchical model by defining the goal, criteria and alternative clusters, adding elements to each cluster, and connecting the elements. The tutorial also provides an overview of performing pairwise comparisons to obtain priority weights in the decision models. The overall purpose is to demonstrate how to use the SuperDecisions software to structurally model decisions and obtain results using AHP or ANP.
This document provides an overview of production systems. It defines the key components of a production system including production rules, working memory, and a recognize-act control cycle. Examples of forward and backward chaining are provided. Advantages such as the separation of knowledge and control and mapping to state space search are discussed. Conflict resolution strategies like refraction, recency and specificity are also summarized.
Proposing an Appropriate Pattern for Car Detection by Using Intelligent Algor...Editor IJCATR
Nowadays, the automotive industry has attracted the attention of consumers, and product quality is considered as an
essential element in current competitive markets. Security and comfort are the main criteria and parameters of selecting a car.
Therefore, standard dataset of CAR involving six features and characteristics and 1728 instances have been used. In this paper, it
has been tried to select a car with the best characteristics by using intelligent algorithms (Random Forest, J48, SVM,
NaiveBayse) and combining these algorithms with aggregated classifiers such as Bagging and AdaBoostMI. In this study, speed
and accuracy of intelligent algorithms in identifying the best car have been taken into account.
This document is a machine learning class assignment submitted by Trushita Redij to their supervisor Abhishek Kaushik at Dublin Business School. The assignment discusses data preprocessing techniques, decision trees, the Chinese Restaurant algorithm, and building supervised learning models. Specifically, linear regression and KNN classification models are implemented on population data from Ireland to predict total population and classify countries.
This chapter discusses multidimensional scaling (MDS) and conjoint analysis. It outlines the key steps in conducting MDS, including formulating the problem, obtaining input data through direct or derived approaches, selecting an MDS procedure, deciding on the number of dimensions, interpreting and labeling the dimensions of the spatial map, and assessing reliability and validity. It also covers assumptions, limitations, and the basic concepts of conjoint analysis.
The document discusses using the Extended Promethee II (EXPROM II) method to determine the best student among alternatives based on multiple criteria. The EXPROM II method is an extension of the Promethee II method for multi-criteria decision making. It involves normalizing data, calculating preference indexes through pairwise comparisons of alternatives, and determining leaving and entering flows to rank alternatives. The document provides an example of applying the EXPROM II method to select the best student among four alternatives based on GPA, leave status, semester performance, and organizational activities.
This document provides an overview of decision making. It defines decision making as selecting a preferred course of action from two or more alternatives. The document outlines the characteristics of operations decisions and the framework for decision making, which involves defining the problem, establishing criteria, generating alternatives, evaluating alternatives, and implementing and monitoring the decision. It also discusses using decision models, including computer-aided models and economic models like break-even analysis, in decision making.
PROVIDING A METHOD FOR DETERMINING THE INDEX OF CUSTOMER CHURN IN INDUSTRYIJITCA Journal
Churn customer, one of the most important issues in customer relationship management and marketing is especially in industries such as telecommunications, the financial and insurance. In recent decades much
research has been done in this area. In this research, the index set for the reasons set reason churn customers for our customers is of particular importance. In this study we are intended to provide a formula for the index churn customers, the better to understand the reasons for customers to provide churn. Therefore, in order to evaluate the formula provided through six Classification methods (Decision tree QUEST, Decision tree C5.0, Decision tree CHAID, Decision trees CART, Bayesian network, Neural network) to evaluate the formula will be involved with individual indicators
Running Head DECISION SUPPORT SYSTEM PLAN 1DECISION SUPPORT.docxsusanschei
Running Head: DECISION SUPPORT SYSTEM PLAN
1
DECISION SUPPORT SYSTEM PLAN
19
Decision Support System Plan - Computer Systems Analysis & Design I
First Name, Last Name
University
IS315
Table of Contents
1.The Scenario
4
2.System Description
4
3.The Process of the Implementation
6
4.Resolution Central Decision Support System
6
4.1Organization’s Information System
6
4.2Key System Benefits
7
5.Feasibility
8
6.Importance of an Information System in the Organization
10
7.Interdependences
11
128.
Feasibility analysis
9.
Project Size………………………………………………………………………………….14
10.
Cost Analysis………………………………………………………………………………..15
18References
List of Figures
Figure 1: The Conceptual Framework
5
Figure 2: The Proposed Model of the System
5
List of Tables
Table 1: The Cost of the Implementation
9
Table 2: The Benefits of the Implementation
9
Decision Support System Plan – Computer Systems Analysis & Design I1. The Scenario
Home Depot is seeking to cut on costs. Some of the areas which have been identified tend to be hot topical issues every time changes are attempted. These include the decision to source products domestically or having them imported. Others include the reduction of the number of employees as well as streamlining service delivery by redefining chores, job assignments, as well as supervision. The business also purposes to put up an information system that will increase positive output and reduce on cost. Even though the choice of the system has been inspired by the kind of challenges which firms like Home Depot experience while attempting trade-offs, it is important to appreciate that this is something that happens with every other organization. Therefore, there is the need for a ‘what if’ scenario so as to analyze situations and come-up with all the possible management outcomes. The issue, therefore, is facilitating the prediction of the behavior of the stakeholders on the basis of certain managerial decisions.2. System Description
The proposed system is called the Resolution Central Decision Support System. This is a Decision Support System, or DSS, that can be exploited by any organization to achieve its streamlining activities. In this case, the dependent variable is enhanced performance. This is defined by increased productivity, enhanced competitive advantage of the organization in question, as well as improvement in customer service. The customers should, actually, be in a position to report that this is the case, i.e. they have seen improvements with respect to how they are treated and their concerns are addressed. Figure I below indicates the conceptual framework. This is the relationship between the ultimate goal and the issues which define this goal.
Figure 1: The Conceptual Framework
The achievement of the goal at hand requires a number of procedures to be accomplished. Planning is the first among them, and then there is the development of the system capability. Ultimately, there is the maturity of the system, and it is at ...
Predicting Employee Attrition using various techniques of Machine LearningIRJET Journal
This document discusses using machine learning techniques to predict employee attrition. It begins with an introduction stating that attrition can negatively impact businesses by requiring rehiring and training of replacement employees. It then reviews related literature on factors that influence attrition like work-life balance and career opportunities.
The document describes the design of predicting attrition using various machine learning algorithms on an employee dataset. It tests algorithms like logistic regression, decision trees, KNN, SVM, random forest and naive bayes. Evaluation shows logistic regression had the highest accuracy at predicting attrition at 87.7%, followed by random forest at 83.2%.
This document presents a new algorithm called UDT-CDF for building decision trees to classify uncertain numerical data. It improves on previous algorithms like UDT that were based on probability density functions (PDFs). The key aspects of the new algorithm are:
1. It uses cumulative distribution functions (CDFs) rather than PDFs to represent uncertain numerical attributes, since CDFs provide more complete probability information.
2. It splits data at decision tree nodes based on the CDF, placing data with values covering the split point into both branches weighted by the CDF.
3. Experimental results show the new CDF-based algorithm achieves more accurate classifications and is more computationally efficient than the PDF-based UDT algorithm,
The Ordered Weighted Averaging (OWA) operator was introduced by Yager [57] to provide a method for aggregating inputs that lie between the max and min operators. In this article two variants of probabilistic extensions the OWA operator-POWA and FPOWA (introduced by Merigo [26] and [27]) are considered as a basis of our generalizations in the environment of fuzzy uncertainty (parts II and III of this work), where different monotone measures (fuzzy measure) are used as uncertainty measures instead of the probability measure. For the identification of “classic” OWA and new operators (presented in parts II and III) of aggregations, the Information Structure is introduced where the incomplete available information in the general decision-making system is presented as a condensation of uncertainty measure, imprecision variable and objective function of weights.
LOAD DISTRIBUTION COMPOSITE DESIGN PATTERN FOR GENETIC ALGORITHM-BASED AUTONO...ijsc
Current autonomic computing systems are ad hoc solutions that are designed and implemented from the
scratch. When designing software, in most cases two or more patterns are to be composed to solve a bigger
problem. A composite design patterns shows a synergy that makes the composition more than just the sum
of its parts which leads to ready-made software architectures. As far as we know, there are no studies on
composition of design patterns for autonomic computing domain. In this paper we propose pattern-oriented
software architecture for self-optimization in autonomic computing system using design patterns
composition and multi objective evolutionary algorithms that software designers and/or programmers can
exploit to drive their work. Main objective of the system is to reduce the load in the server by distributing
the population to clients. We used Case Based Reasoning, Database Access, and Master Slave design
patterns. We evaluate the effectiveness of our architecture with and without design patterns compositions.
The use of composite design patterns in the architecture and quantitative measurements are presented. A
simple UML class diagram is used to describe the architecture.
International Journal of Computational Engineering Research(IJCER)ijceronline
International Journal of Computational Engineering Research(IJCER) is an intentional online Journal in English monthly publishing journal. This Journal publish original research work that contributes significantly to further the scientific knowledge in engineering and Technology.
This technical paper discusses using a 2x2 Cartesian matrix framework to aid structured decision making in project management. The framework involves identifying decision areas, analyzing them to determine attributes, then designing a 2x2 matrix with the attributes on the axes to categorize scenarios into four quadrants. Each quadrant represents a unique decision making scenario requiring an identified action. The paper provides examples of decision matrices for stakeholder management, benefit realization, and governance. It also presents a case study where a company used the framework to help achieve the technology modernization project vision of lower ownership costs through consolidating technology.
Business Bankruptcy Prediction Based on Survival Analysis Approachijcsit
This document discusses business bankruptcy prediction models using survival analysis. It analyzes companies listed on the Taiwan Stock Exchange from 2003 to 2009. The study uses the Cox proportional hazards model to identify key financial ratios that predict business failure. The model includes profitability, leverage, efficiency, and valuation ratios as predictors. The accuracy of the proposed survival analysis model in classifying business failures is 87.93%. The document also discusses other statistical and machine learning techniques used for business bankruptcy prediction, such as logistic regression, neural networks, and hybrid models.
Semantic approach utilizing data mining and case based reasoning for it suppo...eSAT Journals
Abstract Information Technology (IT) plays a very important role in all organizations. IT executives are constantly faced with problems that are difficult to tackle. Failure in IT service can interrupt the functioning of an organization. Case-Based Reasoning (CBR) is a problem solving methodology where experience in the form of past cases can be used to solve problems, thereby assisting the automation of problem solving and experience management. Furthermore, the performance, quality and efficiency of CBR systems can be enhanced through data mining. In order to support the IT team for faster and efficient problem resolution, a case-based reasoning approach integrated with data mining techniques could be utilized. In this paper, the study done on various CBR systems and data mining techniques for problem and experience management is explained. A system is proposed for IT experience and problem management with semantic retrieval in order to increase the efficiency and quality of the IT support service. Keywords: Case-based reasoning, Data Mining, Experience management, IT problem management, IT support.
Semantic approach utilizing data mining and case based reasoning for it suppo...eSAT Publishing House
This document discusses using a semantic approach combining data mining and case-based reasoning to improve IT support services. It proposes a system that uses web crawlers to extract IT problem/solution data from public resources. The data is preprocessed and latent semantic analysis is applied to represent the data semantically in lower dimensions. This allows IT teams to semantically retrieve relevant problem/solution cases from the knowledge base to resolve new issues. The system aims to dynamically increase the IT experience knowledge base and guarantee accurate and efficient case retrieval to enhance IT support service quality and efficiency.
IRJET - An Overview of Machine Learning Algorithms for Data ScienceIRJET Journal
This document provides an overview of machine learning algorithms that are commonly used for data science. It discusses both supervised and unsupervised algorithms. For supervised algorithms, it describes decision trees, k-nearest neighbors, and linear regression. Decision trees create a hierarchical structure to classify data, k-nearest neighbors classifies new data based on similarity to existing data, and linear regression finds a linear relationship between variables. Unsupervised algorithms like clustering are also briefly mentioned. The document aims to familiarize data science enthusiasts with basic machine learning techniques.
Human Resource Recruitment using Fuzzy Decision Making MethodIJSRD
Traditional way of recruiting personnel was through a group decision making problem under multiple criteria containing subjectivity, imprecision and vagueness. In order to keep up with increasing competition of globalization and fast technological improvements and changes, Human resource field needs the best fit employee for a job vacancy. This paper proposes a Fuzzy Decision Making (FDM) method for recruitment process of Human Resource management, which is based on the Fuzzy set theory. Different criteria of human resource recruitment process will be given fuzzy linguistic terms such as absolutely low, extremely low, very low, low, medium, high, very high, extremely high, absolutely high depends upon the importance given by the Human Resource manager. Fuzzy Scaled Weight (FSW) will be calculated for all the criteria. Cumulative Fuzzy Value (CFV) is calculated for all the applicants from Fuzzy Scaled Weight values. Interview Fuzzy Value (IFV) is given by the human resource manager for all the applicants attending interviews. Final Fuzzy Value (FFV) will be calculated aggregating both Cumulative Fuzzy Value and Interview Fuzzy Value. Finally, all the applicant records are arranged in the order of FFV values. Then, Human resource manager can select the applicants easily from the arranged list. Fuzzy Decision Making method system is developed to illustrate the above FDM method for the Human Resource recruitment process.
The document discusses decision support systems (DSS), which are computer-based tools that help decision-makers in organizations solve problems and make decisions. It describes the four stages of decision making - intelligence, design, choice, and implementation. It then explains different types of DSS, including communication-based, data-based, document-based, knowledge-based, and model-based systems. Finally, it discusses benefits of using DSS and group decision support systems.
This document provides a tutorial for using the SuperDecisions software to build decision models using the Analytic Hierarchy Process (AHP) or Analytic Network Process (ANP). It explains the basic concepts of clusters and elements, and how to create a hierarchical model by defining the goal, criteria and alternative clusters, adding elements to each cluster, and connecting the elements. The tutorial also provides an overview of performing pairwise comparisons to obtain priority weights in the decision models. The overall purpose is to demonstrate how to use the SuperDecisions software to structurally model decisions and obtain results using AHP or ANP.
This document provides an overview of production systems. It defines the key components of a production system including production rules, working memory, and a recognize-act control cycle. Examples of forward and backward chaining are provided. Advantages such as the separation of knowledge and control and mapping to state space search are discussed. Conflict resolution strategies like refraction, recency and specificity are also summarized.
Proposing an Appropriate Pattern for Car Detection by Using Intelligent Algor...Editor IJCATR
Nowadays, the automotive industry has attracted the attention of consumers, and product quality is considered as an
essential element in current competitive markets. Security and comfort are the main criteria and parameters of selecting a car.
Therefore, standard dataset of CAR involving six features and characteristics and 1728 instances have been used. In this paper, it
has been tried to select a car with the best characteristics by using intelligent algorithms (Random Forest, J48, SVM,
NaiveBayse) and combining these algorithms with aggregated classifiers such as Bagging and AdaBoostMI. In this study, speed
and accuracy of intelligent algorithms in identifying the best car have been taken into account.
This document is a machine learning class assignment submitted by Trushita Redij to their supervisor Abhishek Kaushik at Dublin Business School. The assignment discusses data preprocessing techniques, decision trees, the Chinese Restaurant algorithm, and building supervised learning models. Specifically, linear regression and KNN classification models are implemented on population data from Ireland to predict total population and classify countries.
This chapter discusses multidimensional scaling (MDS) and conjoint analysis. It outlines the key steps in conducting MDS, including formulating the problem, obtaining input data through direct or derived approaches, selecting an MDS procedure, deciding on the number of dimensions, interpreting and labeling the dimensions of the spatial map, and assessing reliability and validity. It also covers assumptions, limitations, and the basic concepts of conjoint analysis.
Similar to Technique for Order Preference by Similarity to Ideal Solution as Decision Support Method for Determining Employee Performance of Sales Section
The document discusses using the Extended Promethee II (EXPROM II) method to determine the best student among alternatives based on multiple criteria. The EXPROM II method is an extension of the Promethee II method for multi-criteria decision making. It involves normalizing data, calculating preference indexes through pairwise comparisons of alternatives, and determining leaving and entering flows to rank alternatives. The document provides an example of applying the EXPROM II method to select the best student among four alternatives based on GPA, leave status, semester performance, and organizational activities.
This document provides an overview of decision making. It defines decision making as selecting a preferred course of action from two or more alternatives. The document outlines the characteristics of operations decisions and the framework for decision making, which involves defining the problem, establishing criteria, generating alternatives, evaluating alternatives, and implementing and monitoring the decision. It also discusses using decision models, including computer-aided models and economic models like break-even analysis, in decision making.
PROVIDING A METHOD FOR DETERMINING THE INDEX OF CUSTOMER CHURN IN INDUSTRYIJITCA Journal
Churn customer, one of the most important issues in customer relationship management and marketing is especially in industries such as telecommunications, the financial and insurance. In recent decades much
research has been done in this area. In this research, the index set for the reasons set reason churn customers for our customers is of particular importance. In this study we are intended to provide a formula for the index churn customers, the better to understand the reasons for customers to provide churn. Therefore, in order to evaluate the formula provided through six Classification methods (Decision tree QUEST, Decision tree C5.0, Decision tree CHAID, Decision trees CART, Bayesian network, Neural network) to evaluate the formula will be involved with individual indicators
Running Head DECISION SUPPORT SYSTEM PLAN 1DECISION SUPPORT.docxsusanschei
Running Head: DECISION SUPPORT SYSTEM PLAN
1
DECISION SUPPORT SYSTEM PLAN
19
Decision Support System Plan - Computer Systems Analysis & Design I
First Name, Last Name
University
IS315
Table of Contents
1.The Scenario
4
2.System Description
4
3.The Process of the Implementation
6
4.Resolution Central Decision Support System
6
4.1Organization’s Information System
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4.2Key System Benefits
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5.Feasibility
8
6.Importance of an Information System in the Organization
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7.Interdependences
11
128.
Feasibility analysis
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Project Size………………………………………………………………………………….14
10.
Cost Analysis………………………………………………………………………………..15
18References
List of Figures
Figure 1: The Conceptual Framework
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Figure 2: The Proposed Model of the System
5
List of Tables
Table 1: The Cost of the Implementation
9
Table 2: The Benefits of the Implementation
9
Decision Support System Plan – Computer Systems Analysis & Design I1. The Scenario
Home Depot is seeking to cut on costs. Some of the areas which have been identified tend to be hot topical issues every time changes are attempted. These include the decision to source products domestically or having them imported. Others include the reduction of the number of employees as well as streamlining service delivery by redefining chores, job assignments, as well as supervision. The business also purposes to put up an information system that will increase positive output and reduce on cost. Even though the choice of the system has been inspired by the kind of challenges which firms like Home Depot experience while attempting trade-offs, it is important to appreciate that this is something that happens with every other organization. Therefore, there is the need for a ‘what if’ scenario so as to analyze situations and come-up with all the possible management outcomes. The issue, therefore, is facilitating the prediction of the behavior of the stakeholders on the basis of certain managerial decisions.2. System Description
The proposed system is called the Resolution Central Decision Support System. This is a Decision Support System, or DSS, that can be exploited by any organization to achieve its streamlining activities. In this case, the dependent variable is enhanced performance. This is defined by increased productivity, enhanced competitive advantage of the organization in question, as well as improvement in customer service. The customers should, actually, be in a position to report that this is the case, i.e. they have seen improvements with respect to how they are treated and their concerns are addressed. Figure I below indicates the conceptual framework. This is the relationship between the ultimate goal and the issues which define this goal.
Figure 1: The Conceptual Framework
The achievement of the goal at hand requires a number of procedures to be accomplished. Planning is the first among them, and then there is the development of the system capability. Ultimately, there is the maturity of the system, and it is at ...
Predicting Employee Attrition using various techniques of Machine LearningIRJET Journal
This document discusses using machine learning techniques to predict employee attrition. It begins with an introduction stating that attrition can negatively impact businesses by requiring rehiring and training of replacement employees. It then reviews related literature on factors that influence attrition like work-life balance and career opportunities.
The document describes the design of predicting attrition using various machine learning algorithms on an employee dataset. It tests algorithms like logistic regression, decision trees, KNN, SVM, random forest and naive bayes. Evaluation shows logistic regression had the highest accuracy at predicting attrition at 87.7%, followed by random forest at 83.2%.
Harmonized scheme for data mining technique to progress decision support syst...eSAT Journals
Abstract Decision Support System (DSS) is equivalent synonym as management information systems (MIS). Decision supporting systems include also decisions made upon individual data from external sources, management feeling, and various other data sources not included in business intelligence. They serve as an integrated repository for internal and external data-intelligence critical to understanding and evaluating the business within its environmental context. Data mining have emerged to meet this need. With the addition of models, analytic tools, and user interfaces, they have the potential to provide actionable information that supports effective problem and opportunity identification, critical decision-making, and strategy formulation, implementation, and evaluation. The proposed system will support top level management to make a good decision in any time under any uncertain environment. Keywords: Dss, Dm, Mis, Clustering, Classification, Association Rule, K-Mean, Olap, Matlab
The Weights Detection of Multi-Criteria by using Solver IJECEIAES
Multi criteria, which are generally used for decision analysis, have certain characteristics that relate to the purpose of the decision. Multi criteria have complex structures and have different weights depending upon the consideration of assessors and the purpose of the decision also. Expert’s judgment will be used to detect the criteria weights that applied by assessors. The aim of this study is a model to detect the criteria weights and biases on the subcontractor selection and detecting the significant weights, as decisive criteria. A method, which is used to modeling the weights detection, is the Solver Application. Data, totaling 40 sets, has been collected that consist of the assessor’s assessment and the expert’s judgment. The result is a pattern of weights and biases detection. The proposed model have been able to detect of 20 criteria weights and biases, that consist of 4 criteria in the total weights of 60% (as decisive criteria) and 16 criteria in the total weights of 40%. A model has been built by training process performed by the Solver, which the result for MSE training is 9.73711e-08 and for MSE validation is 0.00900528. Novelty in the study is a model to detect pattern of weights criteria and biases on subcontractor selection by transferring the expert's judgment using Solver Application.
The selection of the best employees is one of the process of evaluating how well the performance of the employees is adjusted to the standards set by the company and usually done by top management such as General Manager or Director. In general, the selection of the best employees is still perform manually with many criteria and alternatives, and this usually make it difficult top managerial making decisions as well as the selection of the best employees periodically into a long and complicated process. Therefore, it is necessary to build a decision support system that can help facilitate the decision maker in determining the best choice based on standard criteria, faster, and more objective. In this research, the computational method of decision-making system used is Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). The criteria used in the selection of the best employees are: job responsibilities, work discipline, work quality, and behaviour. The final result of the global priority value of the best employee candidates is used as the best employee selection decision making tool by top management.
Decision Tree Machine Learning Detailed Explanation.DrezzingGaming
Decision Tree is a machine learning algorithm that can be used for both classification and regression problems. It creates a flow-chart like structure starting with an initial node which branches out further into other sub-nodes. The documents discuss decision tree structure, splitting criteria, feature selection and real world applications. Code in Python is provided to demonstrate building a basic decision tree classifier on the iris dataset.
Selection of Equipment by Using Saw and Vikor Methods IJERA Editor
This document discusses methods for selecting equipment using multi-criteria decision making approaches. It presents the SAW (Simple Additive Weighting) and VIKOR (VIseKriterijumska Optimizacija I Kompromisno Resenje) methods for equipment selection. The document outlines the steps for both SAW and VIKOR methods. It also discusses consistency testing to validate the results and ensure less than 0.1 consistency ratio. The methods are then applied to a case study of equipment selection at a spring manufacturing unit to demonstrate the process.
This document discusses decision support systems and risk management. It defines a decision support system as a computer-based system that helps organizational decision making. Decision support systems can help risk managers by analyzing large amounts of data and integrating models to provide information for decision making. The document outlines the characteristics, components, benefits and steps involved in decision support systems. It also defines risk management as identifying potential risks and taking actions to mitigate them. Integrating risk management models into a decision support system can help evaluate risk management decisions.
The series of presentations contains the information about "Management Information System" subject of SEIT for University of Pune.
Subject Teacher: Tushar B Kute (Sandip Institute of Technology and Research Centre, Nashik)
http://www.tusharkute.com
This document describes how to use the Analytic Hierarchy Process (AHP) to make a multi-criteria decision about purchasing an inventory management system. It involves defining the goal, criteria, and alternatives in a hierarchy. Pairwise comparisons are made between criteria and alternatives to assign weights. The weighted scores are calculated and the alternative with the highest score is selected. In this example, the goal is to purchase a system, the criteria are cost, functionality, supplier reputation, and user services, and the alternatives are Systems A, B, and C. System A is determined to have the highest total weighted score, making it the best choice.
The document discusses decision making and decision support systems. It describes decision making as a multi-stage process involving intelligence, design, choice, and implementation. It then defines decision support systems as computer-based tools that help decision makers in the intelligence stage by identifying problems and generating potential solutions. The document outlines different types of decision support systems and their uses.
OPTIMAL ALTERNATIVE SELECTION USING MOORA IN INDUSTRIAL SECTOR - A REVIEWWireilla
Modern manufacturing organizations tend to face versatile challenges due to globalization, modern lifestyle trends and rapid market requirements from both locally and globally placed competitors. The organizations faces high stress from dual perspective namely enhancement in science and technology and development of modern strategies. In such an instance, organizations were in a need of using an effective decision making tool that chooses out optimal alternative that reduces time, complexity and highly simplified. This paper explores a usage of new multi criteria decision making tool known as MOORA for selecting the best alternatives by examining various case study. The study was covered up in two fold manner by comparing MOORA with other MCDM and MADM approaches to identify its advantage for selecting optimal alternative, followed by extending MOORA with interval grey numbers, crisp and interval grey number and whitening coefficient and future scope of the present work concentrate on highlighting the scope and gap between MOORA, Multiplicative form of MOORA(MULTIMOORA) and Multi objective optimization on the basis of simple ratio analysis (MOOSRA) for numerous manufacturing and service applications.
Optimal Alternative Selection Using MOORA in Industrial Sector - A ijfls
Modern manufacturing organizations tend to face versatile challenges due to globalization, modern
lifestyle trends and rapid market requirements from both locally and globally placed competitors. The
organizations faces high stress from dual perspective namely enhancement in science and technology and
development of modern strategies. In such an instance, organizations were in a need of using an effective
decision making tool that chooses out optimal alternative that reduces time, complexity and highly
simplified. This paper explores a usage of new multi criteria decision making tool known as MOORA for
selecting the best alternatives by examining various case study. The study was covered up in two fold
manner by comparing MOORA with other MCDM and MADM approaches to identify its advantage for
selecting optimal alternative, followed by extending MOORA with interval grey numbers, crisp and interval
grey number and whitening coefficient and future scope of the present work concentrate on highlighting the
scope and gap between MOORA, Multiplicative form of MOORA(MULTIMOORA) and Multi objective
optimization on the basis of simple ratio analysis (MOOSRA) for numerous manufacturing and service
applications.
A decision support system (DSS) combines data, models, and software to support decision-making. The document discusses the history and types of DSS, including model-driven DSS which emphasize access and manipulation of models, and data-driven DSS which focus on accessing and analyzing internal and external time-series data. Examples of each type are provided to illustrate how DSS can enhance decision-making in complex, uncertain environments.
A GDSS is an interactive, computer based system that facilitates solution of unstructured problems by a set of decisions makers working together as a group. A GDSS is superior then DSS because in GDSS the decisions are taken by a group of DSS. So it is superior to the DSS." There are three types of GDSS: decision networks, decision rooms, and teleconferencing. The advantages of GDSS include taking better decisions, solving problems, minimizing risk, collecting large amounts of information, providing interactive communication, improving decision making processes, and coordinating activities.
Decision support n system management www.it-workss.comVarunraj Kalse
A GDSS is an interactive, computer based system that facilitates solution of unstructured problems by a set of decisions makers working together as a group. A GDSS is superior then DSS because in GDSS the decisions are taken by a group of DSS. So it is superior to the DSS." There are three types of GDSS: decision networks, decision rooms, and teleconferencing. The advantages of GDSS include taking better decisions, solving problems, minimizing risk, collecting large amounts of information, providing interactive communication, improving decision making processes, and coordinating activities.
Similar to Technique for Order Preference by Similarity to Ideal Solution as Decision Support Method for Determining Employee Performance of Sales Section (20)
The security and speed of data transmission is very important in data communications, the steps that can be done is to use the appropriate cryptographic and compression algorithms in this case is the Data Encryption Standard and Lempel-Ziv-Welch algorithms combined to get the data safe and also the results good compression so that the transmission process can run properly, safely and quickly.
The problem of electric power quality is a matter of changing the form of voltage, current or frequency that can cause failure of equipment, either utility equipment or consumer property. Components of household equipment there are many nonlinear loads, one of which Mixer. Even a load nonlinear current waveform and voltage is not sinusoidal. Due to the use of household appliances such as mixers, it will cause harmonics problems that can damage the electrical system equipment. This study analyzes the percentage value of harmonics in Mixer and reduces harmonics according to standard. Measurements made before the use of LC passive filter yield total current harmonic distortion value (THDi) is 61.48%, while after passive filter use LC the THDi percentage becomes 23.75%. The order of harmonic current in the 3rd order mixer (IHDi) is 0.4185 A not according to standard, after the use of LC passive filter to 0.088 A and it is in accordance with the desired standard, and with the use of passive filter LC, the power factor value becomes better than 0.75 to 0.98.
This paper examines the long-term simultaneous response between dividend policy and corporate value. The main problem studied is that the dividend policy is responded very slowly to the final goal of corporate value. Analysis of Data was using Vector Autoregression (VAR). The result of the discussion concludes the effect of different simultaneous response every period between dividend policy with corporate value, short-term, medium-term, and long-term. The strongest response to dividend changes comes from free cash flow whereas the highest response to corporate value comes from market book value.
Whatsapp is a social media application that is currently widely used from various circles due to ease of use and security is good enough, the security at the time of communicating at this time is very important as well with Whatsapp. Whatsapp from the network is very secure but on the local storage that contains the message was not safe enough because the message on local storage is not secured properly using a special algorithm even using the software Whatsapp Database Viewer whatsapp message can be known, to improve the security of messages on local storage whatsapp submitted security enhancements using the Modular Multiplication Block Cipher algorithm so that the message on whatsapp would be better in terms of security and not easy to read by unauthorized ones.
Consumers are increasingly easy to access to information resources. Consumers quickly interact with whatever they will spend. Ease of use of technology an impact on consumer an attitude are increasingly intelligent and has encouraged the rise of digital transactions. Technology makes it easy for them to transact on an e-commerce shopping channel. Future e-commerce trends will lead to User Generated Content related to user behavior in Indonesia that tends to compare between shopping channels. The purpose of this study was to examine the direct and indirect effects of Perceived Ease of Use on Behavioral Intention to transact in which Perceived Usefulness is used as an intervening variable. The present study used the descriptive exploratory method with causal-predictive analysis. Determination method of research sample used purposive sampling. The enumerator team assists in the distribution of questionnaires. The results of the study found that the direct effect of perceived ease of use on behavioral intention to transact is smaller than that indirectly mediated by perceived usefulness variables.
Performance is a process of assessment of the algorithm. Speed and security is the performance to be achieved in determining which algorithm is better to use. In determining the optimum route, there are two algorithms that can be used for comparison. The Genetic and Primary algorithms are two very popular algorithms for determining the optimum route on the graph. Prim can minimize circuit to avoid connected loop. Prim will determine the best route based on active vertex. This algorithm is especially useful when applied in a minimum spanning tree case. Genetics works with probability properties. Genetics cannot determine which route has the maximum value. However, genetics can determine the overall optimum route based on appropriate parameters. Each algorithm can be used for the case of the shortest path, minimum spanning tree or traveling salesman problem. The Prim algorithm is superior to the speed of Genetics. The strength of the Genetic algorithm lies in the number of generations and population generated as well as the selection, crossover and mutation processes as the resultant support. The disadvantage of the Genetic algorithm is spending to much time to get the desired result. Overall, the Prim algorithm has better performance than Genetic especially for a large number of vertices.
Implementation of Decision Support System for various purposes now can facilitate policy makers to get the best alternative from a variety of predefined criteria, one of the methods used in the implementation of Decision Support System is VIKOR (Vise Kriterijumska Optimizacija I Kompromisno Resenje), VIKOR method in this research got the best results with an efficient and easily understood process computationally, it is expected that the results of this study facilitate various parties to develop a model any solutions.
Edge detection is one of the most frequent processes in digital image processing for various purposes, one of which is detecting road damage based on crack paths that can be checked using a Canny algorithm. This paper proposed a mobile application to detect cracks in the road and with customized threshold function in the requests to produce useful and accurate edge detection. The experimental results show that the use of threshold function in a canny algorithm can detect better damage in the road
The security and confidentiality of information becomes an important factor in communication, the use of cryptography can be a powerful way of securing the information, IDEA (International Data Encryption Algorithm) and WAKE (Word Auto Key Encryption) are some modern symmetric cryptography algorithms with encryption and decryption function are much faster than the asymmetric cryptographic algorithm, with the combination experiment IDEA and WAKE it probable to produce highly secret ciphertext and it hopes to take a very long time for cryptanalyst to decrypt the information without knowing the key of the encryption process.
English is a language that must be known all-digital era at this time where almost all information is in English, ranging from kindergarten to college learn English. elementary school is now also there are learning and to help introduce English is prototype application recogni-tion of common words in English and can be updated dynamically so that updates occur information to new words and sentences in Eng-lish to be introduced to students.
Rabin Karp algorithm is a search algorithm that searches for a substring pattern in a text using hashing. It is beneficial for matching words with many patterns. One of the practical applications of Rabin Karp's algorithm is in the detection of plagiarism. Michael O. Rabin and Richard M. Karp invented the algorithm. This algorithm performs string search by using a hash function. A hash function is the values that are compared between two documents to determine the level of similarity of the document. Rabin-Karp algorithm is not very good for single pattern text search. This algorithm is perfect for multiple pattern search. The Levenshtein algorithm can be used to replace the hash calculation on the Rabin-Karp algorithm. The hash calculation on Rabin-Karp only counts the number of hashes that have the same value in both documents. Using the Levenshtein algorithm, the calculation of the hash distance in both documents will result in better accuracy.
This document summarizes a research paper about violations of cybercrime and jurisdiction in Indonesia. It discusses how technological advances have enabled new forms of digital crime. It describes several types of cybercrimes such as unauthorized access, spreading viruses, hacking, and cyberterrorism. It also discusses Indonesia's laws regarding electronic information and cybercrime. The document analyzes some challenges around jurisdiction for cybercrimes that cross borders. It examines how Indonesia applies legal jurisdiction and sanctions to cybercrime perpetrators based on the location of the crime and perpetrator. It aims to explain how Indonesia's legal system will handle cybercrime cases and reduce such violations.
Competitive market competition so the company must be smart in managing finance. In promoting the selling point, marketing is the most important step to be considered. Promotional routine activity is one of the marketing techniques to increase consumer appeal to marketed products. One of the important agendas of promotion is the selection of the most appropriate promotional media. The problem that often occurs in the process of selecting a promotional media is the subjectivity of decision making. Marketing activities have a taxation fund that must be issued. Limited funds are one of the constraints of improving market strategy. So far, the selection of promotional media is performed by the company manually using standardized determination that already applies. It has many shortcomings, among others, regarding effectiveness and efficiency of time and limited funds. Markov Chain is very helpful to the company in analyzing the development of the company over a period. This method can predict the market share in the future so that company can optimize promotion cost at the certain time. Implementation of this algorithm produces a percentage of market share so that businesses can determine and choose which way is more appropriate to improve the company's market strategy. Assessment is done by looking at consumer criteria of a particular product. These criteria can determine consumer interest in a product so that it can be analyzed consumer behavior.
The transition of copper cable technology to fiber optic is very triggering the development of technology where data can be transmitted quickly and accurately. This cable change can be seen everywhere. This cable is an expensive cable. If it is not installed optimally, it will cost enormously. This excess cost can be used to other things to support performance rather than for excess cable that should be minimized. Determining how much cable use at the time of installation is difficult if done manually. Prim's algorithm can optimize by calculating the minimum spanning tree on branches used for fiber optic cable installation. This algorithm can be used to shorten the time to a destination by making all the points interconnected according to the points listed. Use of this method helps save the cost of fiber optic construction.
An image is a medium for conveying information. The information contained therein may be a particular event, experience or moment. Not infrequently many images that have similarities. However, this level of similarity is not easily detected by the human eye. Eigenface is one technique to calculate the resemblance of an object. This technique calculates based on the intensity of the colors that exist in the two images compared. The stages used are normalization, eigenface, training, and testing. Eigenface is used to calculate pixel proximity between images. This calculation yields the feature value used for comparison. The smallest value of the feature value is an image very close to the original image. Application of this method is very helpful for analysts to predict the likeness of digital images. Also, it can be used in the field of steganography, digital forensic, face recognition and so forth.
The document discusses data compression using Elias Delta coding. It begins by introducing compression and its purpose of reducing file sizes. It then explains Elias Delta coding which is a lossless compression technique that encodes characters based on their frequency. The more common characters have fewer bits assigned while less common characters have more bits. It provides an example of how Elias Delta coding works by assigning bit sequences to numbers. The document then applies Elias Delta coding to compress a sample text, showing the original string, character set formation, bit lengths, and compressed output which achieved a smaller size than the original text.
Technological developments in computer networks increasingly demand security on systems built. Security also requires flexibility, efficiency, and effectiveness. The exchange of information through the internet connection is a common thing to do now. However, this way can be able to trigger data theft or cyber crime which resulted in losses for both parties. Data theft rate is getting higher by using a wireless network. The wireless system does not have any signal restrictions that can be intercepted Filtering is used to restrict incoming access through the internet. It aims to avoid intruders or people who want to steal data. This is fatal if not anticipated. IP and MAC filtering is a way to protect wireless networks from being used and misused by just anyone. This technique is very useful for securing data on the computer if it joins the public network. By registering IP and MAC on a router, this will keep the information unused and stolen. This system is only a few computers that can be connected to a wireless hotspot by IP and MAC Address listed.
Catfish is one type of freshwater fish. This fish has a good taste. In the cultivation of these fish, many obstacles need to be faced. Because living in dirty water, this type of fish is susceptible to disease. Many symptoms arise during the fish cultivation process; From skin disease to physical. Catfish farmers do not know how to diagnose diseases that exist in their livestock. This diagnosis serves to separate places between good and sick catfish. The goal is that the sale value of the fish is high. Catfish that have diseases will be sold cheaper to be used as other animal feed while healthy fish will be sold to the market or exported to other countries. Diagnosis can be done by expert system method. The algorithm of certainty factor is one of the good algorithms to determine the percentage of possible fish disease. This algorithm is very helpful for farmers to improve catfish farming.
Documents do not always have the same content. However, the similarity between documents often occurs in the world of writing scientific papers. Some similarities occur because of a coincidence, but something happens because of the element of intent. On documents that have little content, this can be checked by the eyes. However, on documents that have thousands of lines and pages, of course, it is impossible. To anticipate it, it takes a way that can analyze plagiarism techniques performed. Many methods can examine the resemblance of documents, one of them by using the Rabin-Karp algorithm. The algorithm is very well since it has a determination for syllable cuts (K-Grams). This algorithm looks at how many hash values are the same in both documents. The percentage of plagiarism can also be adjusted up to a few percent according to the need for examination of the document. Implementation of this algorithm is beneficial for an institution to do the filtering of incoming documents. It is usually done at the time of receipt of a scientific paper to be published.
Computer viruses are a nightmare for the computer world. It is a threat to any user who uses a computer network. The computer will not be infected by a virus if the computer is not connected to the outside world. In this case, this is the internet. The Internet can be used as a medium for the spread of the virus to the fullest. There are many types of viruses that are spread through the internet. Some of them are aimed at making money, and there are only as a disrupt activity and computer performance. Some techniques are done to prevent the spread of the virus. Here will be explained how to tackle the virus optimally. The benefit is that the computer used will be free from virus attacks and safe to exchange data publicly. Techniques used include the prevention and prevention of viruses against computer networks are to know the characteristics and workings of the virus.
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إضغ بين إيديكم من أقوى الملازم التي صممتها
ملزمة تشريح الجهاز الهيكلي (نظري 3)
💀💀💀💀💀💀💀💀💀💀
تتميز هذهِ الملزمة بعِدة مُميزات :
1- مُترجمة ترجمة تُناسب جميع المستويات
2- تحتوي على 78 رسم توضيحي لكل كلمة موجودة بالملزمة (لكل كلمة !!!!)
#فهم_ماكو_درخ
3- دقة الكتابة والصور عالية جداً جداً جداً
4- هُنالك بعض المعلومات تم توضيحها بشكل تفصيلي جداً (تُعتبر لدى الطالب أو الطالبة بإنها معلومات مُبهمة ومع ذلك تم توضيح هذهِ المعلومات المُبهمة بشكل تفصيلي جداً
5- الملزمة تشرح نفسها ب نفسها بس تكلك تعال اقراني
6- تحتوي الملزمة في اول سلايد على خارطة تتضمن جميع تفرُعات معلومات الجهاز الهيكلي المذكورة في هذهِ الملزمة
واخيراً هذهِ الملزمة حلالٌ عليكم وإتمنى منكم إن تدعولي بالخير والصحة والعافية فقط
كل التوفيق زملائي وزميلاتي ، زميلكم محمد الذهبي 💊💊
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Chapter wise All Notes of First year Basic Civil Engineering.pptxDenish Jangid
Chapter wise All Notes of First year Basic Civil Engineering
Syllabus
Chapter-1
Introduction to objective, scope and outcome the subject
Chapter 2
Introduction: Scope and Specialization of Civil Engineering, Role of civil Engineer in Society, Impact of infrastructural development on economy of country.
Chapter 3
Surveying: Object Principles & Types of Surveying; Site Plans, Plans & Maps; Scales & Unit of different Measurements.
Linear Measurements: Instruments used. Linear Measurement by Tape, Ranging out Survey Lines and overcoming Obstructions; Measurements on sloping ground; Tape corrections, conventional symbols. Angular Measurements: Instruments used; Introduction to Compass Surveying, Bearings and Longitude & Latitude of a Line, Introduction to total station.
Levelling: Instrument used Object of levelling, Methods of levelling in brief, and Contour maps.
Chapter 4
Buildings: Selection of site for Buildings, Layout of Building Plan, Types of buildings, Plinth area, carpet area, floor space index, Introduction to building byelaws, concept of sun light & ventilation. Components of Buildings & their functions, Basic concept of R.C.C., Introduction to types of foundation
Chapter 5
Transportation: Introduction to Transportation Engineering; Traffic and Road Safety: Types and Characteristics of Various Modes of Transportation; Various Road Traffic Signs, Causes of Accidents and Road Safety Measures.
Chapter 6
Environmental Engineering: Environmental Pollution, Environmental Acts and Regulations, Functional Concepts of Ecology, Basics of Species, Biodiversity, Ecosystem, Hydrological Cycle; Chemical Cycles: Carbon, Nitrogen & Phosphorus; Energy Flow in Ecosystems.
Water Pollution: Water Quality standards, Introduction to Treatment & Disposal of Waste Water. Reuse and Saving of Water, Rain Water Harvesting. Solid Waste Management: Classification of Solid Waste, Collection, Transportation and Disposal of Solid. Recycling of Solid Waste: Energy Recovery, Sanitary Landfill, On-Site Sanitation. Air & Noise Pollution: Primary and Secondary air pollutants, Harmful effects of Air Pollution, Control of Air Pollution. . Noise Pollution Harmful Effects of noise pollution, control of noise pollution, Global warming & Climate Change, Ozone depletion, Greenhouse effect
Text Books:
1. Palancharmy, Basic Civil Engineering, McGraw Hill publishers.
2. Satheesh Gopi, Basic Civil Engineering, Pearson Publishers.
3. Ketki Rangwala Dalal, Essentials of Civil Engineering, Charotar Publishing House.
4. BCP, Surveying volume 1
A Visual Guide to 1 Samuel | A Tale of Two HeartsSteve Thomason
These slides walk through the story of 1 Samuel. Samuel is the last judge of Israel. The people reject God and want a king. Saul is anointed as the first king, but he is not a good king. David, the shepherd boy is anointed and Saul is envious of him. David shows honor while Saul continues to self destruct.
Temple of Asclepius in Thrace. Excavation resultsKrassimira Luka
The temple and the sanctuary around were dedicated to Asklepios Zmidrenus. This name has been known since 1875 when an inscription dedicated to him was discovered in Rome. The inscription is dated in 227 AD and was left by soldiers originating from the city of Philippopolis (modern Plovdiv).
Leveraging Generative AI to Drive Nonprofit InnovationTechSoup
In this webinar, participants learned how to utilize Generative AI to streamline operations and elevate member engagement. Amazon Web Service experts provided a customer specific use cases and dived into low/no-code tools that are quick and easy to deploy through Amazon Web Service (AWS.)
2. 282 International Journal of Engineering & Technology
6) Support the various forms of decision-making and deci-
sion-making processes.
7) Ability to adapt at any time and be flexible.
8) Ease of system interaction.
9) Improving effectiveness in decision-making rather than
efficiency.
10) Easy to develop by expert users.
11) Modeling ability and decision-making analysis.
12) Ease of accessing various sources and data formats.
In addition to the various Characteristics and Abilities as noted
above, DSS also has some limitations as follows:
a. There are some management abilities and human talents that
cannot be modeled, so the models that exist in the system do
not all reflect the real problem.
b. The ability of a DSS is limited to the knowledge that it pos-
sesses (basic knowledge and basic model).
c. The processes that can be performed by the DSS usually
depend also on the software capabilities it uses.
d. DSS does not have the ability of intuition as it is owned by
humans. Because no matter how sophisticated a DSS is, it's
just a collection of hardware, software and operating systems
not equipped with the ability to think.
The TOPSIS method is based on the concept that the best chosen
alternative not only has the shortest distance from the ideal solu-
tion, but also has the longest distance from the ideal solution. This
concept is widely used in some MADM models to solve practical
decision problems[36], [37].
This is because the concept is simple and easy to understand,
computing is efficient, and has the ability to measure the relative
performance of decision alternatives in simple mathematical form.
As for the steps in solving a Multi Attribute Decision Making
(MADM) case with TOPSIS[38]:
a. Make a normalized decision matrix.
b. Make a decision matrix that is normally weighted.
c. Determine the matrix of positive ideal solutions and the ma-
trix of the ideal solution.
d. Determine the distance between the value of each alternative
with a matrix of positive ideal solutions and the ideal nega-
tive solution matrix.
e. Determine the preference value for each alternative.
TOPSIS requires performance rating of each alternative Ai
on loyal Cj normalized criteria.
3. Results and Discussion
The process of applying the Fuzzy Multi Criteria Decision Making
method in performing alternative performance appraisal as follows:
a. Weighting Criteria
Determining the ranking of each alternative, then the first deter-
mination of the importance weight of each criterion (Wj). The
determination of the importance weight of each criterion (Wj) is
formed in Table 1 below.
Table.1: Criteria Weight Value (Wj)
Criteria Weight Value
Data Sales 4
Absence 3
Number of Visits 2
b. Initial Data of each alternative
From the criterion data already started, the next step is to deter-
mine the match rating as Table 2 below:
Table.2: Alternative
Alternative
Criteria
C1 C2 C3
Alternative 1 3 2 3
Alternative 2 2 2 3
Alternative 3 4 1 3
After the initial data obtained from each alternative, then begins
calculation of Fuzzy Multi Criteria Decision Making method by
building a decision matrix. In the decision matrix, the matrix col-
umn expresses the attributes of the existing criteria, while the
matrix line represents the alternative. The decision matrix refers to
the alternative m that will be evaluated on the basis of n criteria.
Decision matrix can be seen in table 3 that is:
Table.3: Decision Matrix
Alternative
Criteria
C1 C2 C3
Alternative 1 X11 X12 X13
Alternative 2 X21 X22 X23
Alternative 3 X31 X32 X33
Next is to create a normalized R decision matrix whose function is
to minimize the range of data, with the aim of making it possible
to calculate Fuzzy Multi Criteria Decision Making.
Table.4: Matrix Normalized
Criteria
C1 C2 C3
A1
√ √ √
A2
√ √ √
A3
√ √ √
So the result of normalized matrix is seen in the following calcula-
tion:
A1 (Criteria 1)
√
√
√
(Criteria 2)
√
√
√
(Criteria 3)
√
√
√
A2 (Criteria 1)
√
√
√
3. International Journal of Engineering & Technology 283
(Criteria 2)
√
√
√
(Criteria 3)
√
√
√
A3 (Criteria 1)
√
√
√
A3 (Criteria 2)
√
√
√
(Criteria 3)
√
√
√
After the decision matrix has normalized the next step is to create
a weighted normalized matrix V whose elements are determined
by the formula:
Table.5: Weight Matrix Normalized
No Alternative Criteria
1 A1
2 A2
3 A3
So the results of calculations on weighted normalized matrices can
be seen in table 6.
Table.6: Results of normalized Matrices are weighted
No Alternative Criteria
1 A1 2.23 2.00 1.15
2 A2 1.49 2.00 1.15
3 A3 2.97 1.00 1.15
After performing the above stages then the next stage determines
the ideal positive solution matrix (A +) and the ideal solution (A-).
The A + value is derived from the highest value of each criterion
while the A-value is derived from the lowest value. The second
criterion, there are 3 values that are 2.23, 1.49 and 2.97, then the
highest value is 2.97 while the lowest value is 1.49, means for the
second criterion, A + = 2.97 and A- = 1.49.
The distance of the positive ideal solution is the total distance
difference between each normalized weighted matrix value with
its maximum value while the ideal negative solution distance is
the total distance difference between each weighted normalized
matrix with its minimum value. Then obtained the value of S +
and S- of each alternative as follows:
A+
1
√
( ) ( ) ( )
√
( ) ( ) ( )
√
( ) ( )
√
√
0.74
A-
1
√
( ) ( ) ( )
√
( ) ( ) ( )
√
( ) ( )
√
√
=1,24
A+
2
√
( ) ( ) ( )
√
( ) ( ) ( )
√
( ) ( )
√
√
1.48
A-
2
√
( ) ( ) ( )
√
( ) ( ) ( )
√
( ) ( )
4. 284 International Journal of Engineering & Technology
√
√
=1
A+
3
√
( ) ( ) ( )
√
( ) ( ) ( )
√
( ) ( ) ( )
√
√
1
A-
3
√
( ) ( ) ( )
√
( ) ( ) ( )
√
( ) ( ) ( )
√
√
=1,48
After calculating S + and S- then the next step is calculating the
proximity relative to the ideal solution (C), so the result of the C
value of each alternative can be calculated as follows:
A1
=0.63
A2
=0.40
A3
=0.60
So at the value of each alternative can be sorted to know which
alternative is best.
4. Conclusion
The application of TOPSIS method to determine the best salesman
can run well, positive and negative ideal concept can give compar-
ison between each alternative of each criterion, this research is far
from good and the results obtained also only based on one method
only and for further development can be combined or compared
with other methods to obtain varying results
.
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