This document discusses using data mining techniques like decision trees and CHAID algorithms to analyze disciplinary records from a university's Student Welfare and Formation Office. It aims to identify relationships between student demographics and offense categories to develop an efficient remediation plan. The study uses Data Envelopment Analysis to evaluate the efficiency of different colleges in minimizing student offenses. Classification decision trees and CHAID analysis identify that most students commit minor offenses regardless of attributes like gender or year level. The results will inform a Student Offenses Remediation System to efficiently address issues and improve university services.
Efficiency of Women’s Technical Institutions By Using Bcc Model Through Dea A...IOSR Journals
This paper conducts an application of the DEA Methodology in the assessment of the performance of JNTUH Colleges the indicators included the Faculty, Students, Infrastructure and Placements of the technical Institutions. The results reveal those institutions that more efficiently carry out these activities. The proposed method has been used for selection of quality attributes in technical education setting the performance of an institute is likely to be influenced by quality of teacher, quality of students, infrastructure administration, extent of training and placement and many others. It is felt that quality and performance evaluation is necessary not only for appraisal but it is also required to improve overall service quality. Finally we discuss about the existence of differences in the strengths and weaknesses between the technical institutions.
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.
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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Recent Database Management Systems Research Articles - September 2020ijdms
Recent Database Management Systems
Research Articles - September 2020
International Journal of Database Management Systems (IJDMS)
ISSN: 0975-5705 (Online); 0975-5985 (Print)
http://airccse.org/journal/ijdms/index.html
Contact us: ijdmsjournal@airccse.org
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.
Efficiency of Women’s Technical Institutions By Using Bcc Model Through Dea A...IOSR Journals
This paper conducts an application of the DEA Methodology in the assessment of the performance of JNTUH Colleges the indicators included the Faculty, Students, Infrastructure and Placements of the technical Institutions. The results reveal those institutions that more efficiently carry out these activities. The proposed method has been used for selection of quality attributes in technical education setting the performance of an institute is likely to be influenced by quality of teacher, quality of students, infrastructure administration, extent of training and placement and many others. It is felt that quality and performance evaluation is necessary not only for appraisal but it is also required to improve overall service quality. Finally we discuss about the existence of differences in the strengths and weaknesses between the technical institutions.
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.
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.
Website Visit: https://bit.ly/3dANXUD
Contact Us:
UK NO: +44-1143520021
India No: +91-8754446690
Email: info@phdassistance.com
Recent Database Management Systems Research Articles - September 2020ijdms
Recent Database Management Systems
Research Articles - September 2020
International Journal of Database Management Systems (IJDMS)
ISSN: 0975-5705 (Online); 0975-5985 (Print)
http://airccse.org/journal/ijdms/index.html
Contact us: ijdmsjournal@airccse.org
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.
Download Link > https://ertekprojects.com/gurdal-ertek-publications/blog/modelling-the-supply-chain-perception-gaps/
This study applies the research of perception gap analysis to supply chain integration and develops a generic model, the 3-Level Gaps Model, with the goal of contributing to harmonization and integration in the supply chain. The model suggests that significant perception gaps may exist among supply chain members with regards to the importance of different performance criteria. The concept of the model is conceived through an empirical and inductive approach, combining the research discipline of supply chain relationship and perception gap analysis. First hand data has been collected through a survey across a key buyer in the motor insurance industry and its eight suppliers. Rigorous statistical analysis testified the research hypotheses, which in turn verified the validity and relevance of the developed 3-Level Gaps Model. The research reveals the significant existence of supply chain perception gaps at all three levels as defined, which could be the root-causes to underperformed supply chain.
Credit Scoring Using CART Algorithm and Binary Particle Swarm Optimization IJECEIAES
Credit scoring is a procedure that exists in every financial institution. A way to predict whether the debtor was qualified to be given the loan or not and has been a major concern in the overall steps of the loan process. Almost all banks and other financial institutions have their own credit scoring methods. Nowadays, data mining approach has been accepted to be one of the wellknown methods. Certainly, accuracy was also a major issue in this approach. This research proposed a hybrid method using CART algorithm and Binary Particle Swarm Optimization. Performance indicators that are used in this research are classification accuracy, error rate, sensitivity, specificity, and precision. Experimental results based on the public dataset showed that the proposed method accuracy is 78 % and 87.53 %. In compare to several popular algorithms, such as neural network, logistic regression and support vector machine, the proposed method showed an outstanding performance.
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.
PREDICTING ACADEMIC MAJOR OF STUDENTS USING BAYESIAN NETWORKS TO THE CASE OF ...ijcax
In this study, which took place current year in the city of Maragheh in IRAN. Number of high school students in the fields of study: mathematics, Experimental Sciences, humanities, vocational, business and science were studied and compared. The purpose of this research is to predict the academic major of high school students using Bayesian networks. The effective factors have been used in academic major selection for the first time as an effective indicator of Bayesian networks. Evaluation of Impacts of indicators on each other, discretization data and processing them was performed by GeNIe. The proper course would be advised for students to continue their education.
Data Mining Application in Advertisement Management of Higher Educational Ins...ijcax
In recent years, Indian higher educational institute’s competition grows rapidly for attracting students to get enrollment in their institutes. To attract students educational institutes select a best advertisement method. There are different advertisements available in the market but a selection of them is very difficult
for institutes. This paper is helpful for institutes to select a best advertisement medium using some data mining methods.
Technical Efficiency of Management wise Schools in Secondary School Examinati...IOSRJM
In this paper we measuring the Board of Secondary education data by CCR Model for the Andhra Pradesh state for the academic years 2012-2013 and 2013-2014 to see the Pattern through CCR Technical Efficiency of the Management wise school results in prior to the division of state in to two separate states. The Performance of the Management wise schools are presented along with the Peer Management Schools performance of the state as a whole.
Identification of important features and data mining classification technique...IJECEIAES
Employees absenteeism at the work costs organizations billions a year. Prediction of employees’ absenteeism and the reasons behind their absence help organizations in reducing expenses and increasing productivity. Data mining turns the vast volume of human resources data into information that can help in decision-making and prediction. Although the selection of features is a critical step in data mining to enhance the efficiency of the final prediction, it is not yet known which method of feature selection is better. Therefore, this paper aims to compare the performance of three well-known feature selection methods in absenteeism prediction, which are relief-based feature selection, correlation-based feature selection and information-gain feature selection. In addition, this paper aims to find the best combination of feature selection method and data mining technique in enhancing the absenteeism prediction accuracy. Seven classification techniques were used as the prediction model. Additionally, cross-validation approach was utilized to assess the applied prediction models to have more realistic and reliable results. The used dataset was built at a courier company in Brazil with records of absenteeism at work. Regarding experimental results, correlationbased feature selection surpasses the other methods through the performance measurements. Furthermore, bagging classifier was the best-performing data mining technique when features were selected using correlation-based feature selection with an accuracy rate of (92%).
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.
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
Dissertation data analysis in management science tutors india.com for my man...Tutors India
Management Science is very much crucial in management decision making. The primary purpose of decision-making is for effective and efficient utilization of scarce or the limited resources for which there are both private and public sectors of that economy. The present article helps the USA, the UK, Europe and the Australian students pursuing their master’s degree to identify the best data analysis, which is usually considered to be challenging. Tutors India offers UK dissertation in various Domains.
When you Order any reflective report at Tutors India, we promise you the following
Plagiarism free
Always on Time
Outstanding customer support
Written to Standard
Unlimited Revisions support
High-quality Subject Matter Experts.
Contact:
Website: www.tutorsindia.com
Email: info@tutorsindia.com
United Kingdom: +44-1143520021
India: +91-4448137070
Whatsapp Number: +91-8754446690
Reference: http://bit.ly/3bIMnzo
Selecting Experts Using Data Quality Conceptsijdms
Personal networks are not always diverse or large enough to reach those with the right information. This
problem increases when assembling a group of experts from around the world, something which is a
challenge in Future-oriented Technology Analysis (FTA). In this work, we address the formation of a panel
of experts, specifically how to select a group of experts from a huge group of people. We propose an
approach which uses data quality dimensions to improve expert selection quality and provide quality
metrics to the forecaster. We performed a case study and successfully showed that it is possible to use data
quality methods to support the expert search process.
The recruitment of new personnel is one of the most essential business processes which affect the quality of
human capital within any company. It is highly essential for the companies to ensure the recruitment of
right talent to maintain a competitive edge over the others in the market. However IT companies often face
a problem while recruiting new people for their ongoing projects due to lack of a proper framework that
defines a criteria for the selection process. In this paper we aim to develop a framework that would allow
any project manager to take the right decision for selecting new talent by correlating performance
parameters with the other domain-specific attributes of the candidates. Also, another important motivation
behind this project is to check the validity of the selection procedure often followed by various big
companies in both public and private sectors which focus only on academic scores, GPA/grades of students
from colleges and other academic backgrounds. We test if such a decision will produce optimal results in
the industry or is there a need for change that offers a more holistic approach to recruitment of new talent
in the software companies. The scope of this work extends beyond the IT domain and a similar procedure
can be adopted to develop a recruitment framework in other fields as well. Data-mining techniques provide
useful information from the historical projects depending on which the hiring-manager can make decisions
for recruiting high-quality workforce. This study aims to bridge this hiatus by developing a data-mining
framework based on an ensemble-learning technique to refocus on the criteria for personnel selection. The
results from this research clearly demonstrated that there is a need to refocus on the selection-criteria for
quality objectives.
Multi Criteria Decision Making Methodology on Selection of a Student for All ...ijtsrd
Selecting a student for all round excellent award is based on a complex, elaborate combination of abilities and skills. A multi criteria Decision Making method, AHP is used to help in making decision consistently by doing a pairwise comparison matrix process between criteria based on selected alternatives and determining the priority order of criteria and alternatives used. The results of these calculations are used to determine the outstanding student receiving a scholarship based on the final results of the AHP method calculation. The results demonstrated that the student ranking is more likely influenced by the relative importance of management, leadership and motivation by sub criteria, education, cooperation, innovation, disciplinary, attendance, knowledge, sports activity, social activity and awards. Kyi Kyi Mynit "Multi Criteria Decision Making Methodology on Selection of a Student for All Round Excellent Award" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd26428.pdfPaper URL: https://www.ijtsrd.com/management/research-method/26428/multi-criteria-decision-making-methodology-on-selection-of-a-student-for-all-round-excellent-award/kyi-kyi-mynit
Correlation based feature selection (cfs) technique to predict student perfro...IJCNCJournal
Education data mining is an emerging stream which h
elps in mining academic data for solving various
types of problems. One of the problems is the selec
tion of a proper academic track. The admission of a
student in engineering college depends on many fact
ors. In this paper we have tried to implement a
classification technique to assist students in pred
icting their success in admission in an engineering
stream.We have analyzed the data set containing inf
ormation about student’s academic as well as socio-
demographic variables, with attributes such as fami
ly pressure, interest, gender, XII marks and CET ra
nk
in entrance examinations and historical data of pre
vious batch of students. Feature selection is a pro
cess
for removing irrelevant and redundant features whic
h will help improve the predictive accuracy of
classifiers. In this paper first we have used featu
re selection attribute algorithms Chi-square.InfoGa
in, and
GainRatio to predict the relevant features. Then we
have applied fast correlation base filter on given
features. Later classification is done using NBTree
, MultilayerPerceptron, NaiveBayes and Instance bas
ed
–K- nearest neighbor. Results showed reduction in c
omputational cost and time and increase in predicti
ve
accuracy for the student model
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.
Recommendation of Data Mining Technique in Higher Education Prof. Priya Thaka...ijceronline
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
Download Link > https://ertekprojects.com/gurdal-ertek-publications/blog/modelling-the-supply-chain-perception-gaps/
This study applies the research of perception gap analysis to supply chain integration and develops a generic model, the 3-Level Gaps Model, with the goal of contributing to harmonization and integration in the supply chain. The model suggests that significant perception gaps may exist among supply chain members with regards to the importance of different performance criteria. The concept of the model is conceived through an empirical and inductive approach, combining the research discipline of supply chain relationship and perception gap analysis. First hand data has been collected through a survey across a key buyer in the motor insurance industry and its eight suppliers. Rigorous statistical analysis testified the research hypotheses, which in turn verified the validity and relevance of the developed 3-Level Gaps Model. The research reveals the significant existence of supply chain perception gaps at all three levels as defined, which could be the root-causes to underperformed supply chain.
Credit Scoring Using CART Algorithm and Binary Particle Swarm Optimization IJECEIAES
Credit scoring is a procedure that exists in every financial institution. A way to predict whether the debtor was qualified to be given the loan or not and has been a major concern in the overall steps of the loan process. Almost all banks and other financial institutions have their own credit scoring methods. Nowadays, data mining approach has been accepted to be one of the wellknown methods. Certainly, accuracy was also a major issue in this approach. This research proposed a hybrid method using CART algorithm and Binary Particle Swarm Optimization. Performance indicators that are used in this research are classification accuracy, error rate, sensitivity, specificity, and precision. Experimental results based on the public dataset showed that the proposed method accuracy is 78 % and 87.53 %. In compare to several popular algorithms, such as neural network, logistic regression and support vector machine, the proposed method showed an outstanding performance.
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.
PREDICTING ACADEMIC MAJOR OF STUDENTS USING BAYESIAN NETWORKS TO THE CASE OF ...ijcax
In this study, which took place current year in the city of Maragheh in IRAN. Number of high school students in the fields of study: mathematics, Experimental Sciences, humanities, vocational, business and science were studied and compared. The purpose of this research is to predict the academic major of high school students using Bayesian networks. The effective factors have been used in academic major selection for the first time as an effective indicator of Bayesian networks. Evaluation of Impacts of indicators on each other, discretization data and processing them was performed by GeNIe. The proper course would be advised for students to continue their education.
Data Mining Application in Advertisement Management of Higher Educational Ins...ijcax
In recent years, Indian higher educational institute’s competition grows rapidly for attracting students to get enrollment in their institutes. To attract students educational institutes select a best advertisement method. There are different advertisements available in the market but a selection of them is very difficult
for institutes. This paper is helpful for institutes to select a best advertisement medium using some data mining methods.
Technical Efficiency of Management wise Schools in Secondary School Examinati...IOSRJM
In this paper we measuring the Board of Secondary education data by CCR Model for the Andhra Pradesh state for the academic years 2012-2013 and 2013-2014 to see the Pattern through CCR Technical Efficiency of the Management wise school results in prior to the division of state in to two separate states. The Performance of the Management wise schools are presented along with the Peer Management Schools performance of the state as a whole.
Identification of important features and data mining classification technique...IJECEIAES
Employees absenteeism at the work costs organizations billions a year. Prediction of employees’ absenteeism and the reasons behind their absence help organizations in reducing expenses and increasing productivity. Data mining turns the vast volume of human resources data into information that can help in decision-making and prediction. Although the selection of features is a critical step in data mining to enhance the efficiency of the final prediction, it is not yet known which method of feature selection is better. Therefore, this paper aims to compare the performance of three well-known feature selection methods in absenteeism prediction, which are relief-based feature selection, correlation-based feature selection and information-gain feature selection. In addition, this paper aims to find the best combination of feature selection method and data mining technique in enhancing the absenteeism prediction accuracy. Seven classification techniques were used as the prediction model. Additionally, cross-validation approach was utilized to assess the applied prediction models to have more realistic and reliable results. The used dataset was built at a courier company in Brazil with records of absenteeism at work. Regarding experimental results, correlationbased feature selection surpasses the other methods through the performance measurements. Furthermore, bagging classifier was the best-performing data mining technique when features were selected using correlation-based feature selection with an accuracy rate of (92%).
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.
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
Dissertation data analysis in management science tutors india.com for my man...Tutors India
Management Science is very much crucial in management decision making. The primary purpose of decision-making is for effective and efficient utilization of scarce or the limited resources for which there are both private and public sectors of that economy. The present article helps the USA, the UK, Europe and the Australian students pursuing their master’s degree to identify the best data analysis, which is usually considered to be challenging. Tutors India offers UK dissertation in various Domains.
When you Order any reflective report at Tutors India, we promise you the following
Plagiarism free
Always on Time
Outstanding customer support
Written to Standard
Unlimited Revisions support
High-quality Subject Matter Experts.
Contact:
Website: www.tutorsindia.com
Email: info@tutorsindia.com
United Kingdom: +44-1143520021
India: +91-4448137070
Whatsapp Number: +91-8754446690
Reference: http://bit.ly/3bIMnzo
Selecting Experts Using Data Quality Conceptsijdms
Personal networks are not always diverse or large enough to reach those with the right information. This
problem increases when assembling a group of experts from around the world, something which is a
challenge in Future-oriented Technology Analysis (FTA). In this work, we address the formation of a panel
of experts, specifically how to select a group of experts from a huge group of people. We propose an
approach which uses data quality dimensions to improve expert selection quality and provide quality
metrics to the forecaster. We performed a case study and successfully showed that it is possible to use data
quality methods to support the expert search process.
The recruitment of new personnel is one of the most essential business processes which affect the quality of
human capital within any company. It is highly essential for the companies to ensure the recruitment of
right talent to maintain a competitive edge over the others in the market. However IT companies often face
a problem while recruiting new people for their ongoing projects due to lack of a proper framework that
defines a criteria for the selection process. In this paper we aim to develop a framework that would allow
any project manager to take the right decision for selecting new talent by correlating performance
parameters with the other domain-specific attributes of the candidates. Also, another important motivation
behind this project is to check the validity of the selection procedure often followed by various big
companies in both public and private sectors which focus only on academic scores, GPA/grades of students
from colleges and other academic backgrounds. We test if such a decision will produce optimal results in
the industry or is there a need for change that offers a more holistic approach to recruitment of new talent
in the software companies. The scope of this work extends beyond the IT domain and a similar procedure
can be adopted to develop a recruitment framework in other fields as well. Data-mining techniques provide
useful information from the historical projects depending on which the hiring-manager can make decisions
for recruiting high-quality workforce. This study aims to bridge this hiatus by developing a data-mining
framework based on an ensemble-learning technique to refocus on the criteria for personnel selection. The
results from this research clearly demonstrated that there is a need to refocus on the selection-criteria for
quality objectives.
Multi Criteria Decision Making Methodology on Selection of a Student for All ...ijtsrd
Selecting a student for all round excellent award is based on a complex, elaborate combination of abilities and skills. A multi criteria Decision Making method, AHP is used to help in making decision consistently by doing a pairwise comparison matrix process between criteria based on selected alternatives and determining the priority order of criteria and alternatives used. The results of these calculations are used to determine the outstanding student receiving a scholarship based on the final results of the AHP method calculation. The results demonstrated that the student ranking is more likely influenced by the relative importance of management, leadership and motivation by sub criteria, education, cooperation, innovation, disciplinary, attendance, knowledge, sports activity, social activity and awards. Kyi Kyi Mynit "Multi Criteria Decision Making Methodology on Selection of a Student for All Round Excellent Award" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd26428.pdfPaper URL: https://www.ijtsrd.com/management/research-method/26428/multi-criteria-decision-making-methodology-on-selection-of-a-student-for-all-round-excellent-award/kyi-kyi-mynit
Correlation based feature selection (cfs) technique to predict student perfro...IJCNCJournal
Education data mining is an emerging stream which h
elps in mining academic data for solving various
types of problems. One of the problems is the selec
tion of a proper academic track. The admission of a
student in engineering college depends on many fact
ors. In this paper we have tried to implement a
classification technique to assist students in pred
icting their success in admission in an engineering
stream.We have analyzed the data set containing inf
ormation about student’s academic as well as socio-
demographic variables, with attributes such as fami
ly pressure, interest, gender, XII marks and CET ra
nk
in entrance examinations and historical data of pre
vious batch of students. Feature selection is a pro
cess
for removing irrelevant and redundant features whic
h will help improve the predictive accuracy of
classifiers. In this paper first we have used featu
re selection attribute algorithms Chi-square.InfoGa
in, and
GainRatio to predict the relevant features. Then we
have applied fast correlation base filter on given
features. Later classification is done using NBTree
, MultilayerPerceptron, NaiveBayes and Instance bas
ed
–K- nearest neighbor. Results showed reduction in c
omputational cost and time and increase in predicti
ve
accuracy for the student model
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.
Recommendation of Data Mining Technique in Higher Education Prof. Priya Thaka...ijceronline
International Journal of Computational Engineering Research (IJCER) is dedicated to protecting personal information and will make every reasonable effort to handle collected information appropriately. All information collected, as well as related requests, will be handled as carefully and efficiently as possible in accordance with IJCER standards for integrity and objectivity.
APPLYING DATA ENVELOPMENT ANALYSIS AND CLUSTERING ANALYSIS IN ENHANCING THE P...IJITCA Journal
Data envelopment analysis is a technique or method for assessing and evaluating the relative performance of organizational entities where the manifestation of multiple inputs and outputs makes comparison difficult. Efficiency was measured through data envelopment analysis in Philippine National Police District VI in the Province of Cavite to measure the performance of decision-making units in terms of their
resources. Clustering is the process of grouping and analyzing the list of objects which have similar characteristics. Clustering algorithm is used in this study to help identify crime pattern. The clustering algorithm was implemented in the application software Crime Management System (CriMS) to predict the
crime pattern to help Philippine National Police District VI in the Province of Cavite in decreasing the total number of crime volume and increase the number of crimes solved to countervail security concerns of an individual, community, and the state. Further studies must be conducted to determine the usefulness of the application software by leading to an empirical study on the rule set used to determine the predictive accuracy and/or software productivity.
APPLYING DATA ENVELOPMENT ANALYSIS AND CLUSTERING ANALYSIS IN ENHANCING THE P...IJITCA Journal
Data envelopment analysis is a technique or method for assessing and evaluating the relative performance
of organizational entities where the manifestation of multiple inputs and outputs makes comparison
difficult. Efficiency was measured through data envelopment analysis in Philippine National Police District
VI in the Province of Cavite to measure the performance of decision-making units in terms of their
resources. Clustering is the process of grouping and analyzing the list of objects which have similar
characteristics. Clustering algorithm is used in this study to help identify crime pattern. The clustering
algorithm was implemented in the application software Crime Management System (CriMS) to predict the
crime pattern to help Philippine National Police District VI in the Province of Cavite in decreasing the
total number of crime volume and increase the number of crimes solved to countervail security concerns of
an individual, community, and the state. Further studies must be conducted to determine the usefulness of
the application software by leading to an empirical study on the rule set used to determine the predictive
accuracy and/or software productivity.
APPLYING DATA ENVELOPMENT ANALYSIS AND CLUSTERING ANALYSIS IN ENHANCING THE P...IJITCA Journal
Data envelopment analysis is a technique or method for assessing and evaluating the relative performance of organizational entities where the manifestation of multiple inputs and outputs makes comparison difficult. Efficiency was measured through data envelopment analysis in Philippine National Police District VI in the Province of Cavite to measure the performance of decision-making units in terms of their resources. Clustering is the process of grouping and analyzing the list of objects which have similar characteristics. Clustering algorithm is used in this study to help identify crime pattern. The clustering algorithm was implemented in the application software Crime Management System (CriMS) to predict thecrime pattern to help Philippine National Police District VI in the Province of Cavite in decreasing the total number of crime volume and increase the number of crimes solved to countervail security concerns of an individual, community, and the state. Further studies must be conducted to determine the usefulness of the application software by leading to an empirical study on the rule set used to determine the predictive accuracy and/or software productivity.
APPLYING DATA ENVELOPMENT ANALYSIS AND CLUSTERING ANALYSIS IN ENHANCING THE P...IJITCA Journal
Data envelopment analysis is a technique or method for assessing and evaluating the relative performance of organizational entities where the manifestation of multiple inputs and outputs makes comparison difficult. Efficiency was measured through data envelopment analysis in Philippine National Police District VI in the Province of Cavite to measure the performance of decision-making units in terms of their resources. Clustering is the process of grouping and analyzing the list of objects which have similar characteristics. Clustering algorithm is used in this study to help identify crime pattern. The clustering algorithm was implemented in the application software Crime Management System (CriMS) to predict the crime pattern to help Philippine National Police District VI in the Province of Cavite in decreasing the total number of crime volume and increase the number of crimes solved to countervail security concerns of an individual, community, and the state. Further studies must be conducted to determine the usefulness of the application software by leading to an empirical study on the rule set used to determine the predictive accuracy and/or software productivity.
LABELING CUSTOMERS USING DISCOVERED KNOWLEDGE CASE STUDY: AUTOMOBILE INSURAN...ijmvsc
In this paper, we used the knowledge discovery in databases and data mining, one of the data-based decision support techniques to help labeling customers in the automobile insurance industry. In most data mining application cases, major tasks including data preparation, data preprocessing, data transformation, data mining, interpretation, application and evaluation, are required. The results of a case study are presented that knowledge discovery of databases and data mining is used to explore decision rules for an automobile insurance company. The decision rules can be used to label the customers as “bad” or “good” for insurance policies.
Our Journal has became fully open access Journal. It’s publishes Differential Equations, Operations Research Mathematical Economics etc.UMJ is an original research in Pure and Applied Mathematics and Statistics. UMJ coverage extends to Operations Research, Mathematical Economics, Mathematics Biology and Computer Science.
Internet becomes the most popular surfing environment which increases the
service oriented data size. As the data size grows, finding and retrieving the most
similar data from the large volume of data would become more difficult task. This
problem is focused in the various research methods, which attempts to cluster the
large volume of data. In the existing research method Clustering-based Collaborative
Filtering approach (ClubCF) is introduced whose main goal is to cluster the similar
kind of data together, so that retrieval time cost can be reduced considerably.
However, existing research methods cannot find the similar reviews accurately which
needs to be focused more for efficient and accurate recommendation system. This is
ensured in the proposed research method by introducing the novel research technique
namely Modified Collaborative Filtering and Clustering with Regression (MoCFCR).
In this research method, initially k means algorithm is used to cluster the similar
movie reviewer together, so that recommendation process can be done in the easier
way. In order to handle the large volume of data this research work adapts the map
reduce framework which will divide the entire data into subsets which will assigned
on separate nodes with individual key values. After clustering, the clustered outcome
is merged together using inverted index procedure in which similarity between movies
would be calculated. Here collaborative filtering is applied to remove the movies that
are not relevant to input. Finally recommendations of movies are made in the accurate
way by using the logistic regression method. The overall evaluation of the proposed
research method is done in Hadoop from which it can be proved that the proposed
research technique can lead to provide better outcome than the existing research
techniques
Classification and visualization: Twitter sentiment analysis of Malaysia’s pr...IAESIJAI
Malaysia has many private’s hospitals. Thus, feedback is important to improve service quality, becoming reviews for other patients. Reviews use the channel service provided on social media, such as Twitter. Nevertheless, online reviews are unstructured and enormous in volume, which leads to difficulties in comparing private hospitals. In addition, no single websites compare private hospitals based on users’ interests, bilingual reviews, and less time-consuming. Due to that, this study aims to classify and visualize the Twitter sentiment analysis of private hospitals in Malaysia. The scope focuses on five factors: 1) administrative procedure, 2) cost, 3) communication, 4) expertise, and 5) service. Term frequency-inverse document frequency is used for text mining, information retrieval techniques, and the Naïve Bayes, a machine learning algorithm for the classification. The user can visualize the specified state’s private hospitals and compare them with any selected state. The system’s functionality and usability have been tested to ensure it meets the objectives. Functionality testing proved that the private hospital’s Twitter sentiment could be predicted based on the training and testing data as intended, with 77.13% and 77.96% accuracy for English and Bahasa Melayu, respectively, while the system usability scale based on the usability testing resulted in an average final score of 95.42%.
The increasing need for data driven decision making recently has resulted in the application of data mining in various fields including the educational sector which is referred to as educational data mining. The need for improving the performance of data mining models has also been identified as a gap for future researcher. In Nigeria, higher educational institutions collect various students’ data, but these data are rarely used in any decision or policy making to improve the academic performance of students. This research work, attempts to improve the performance of data mining models for predicting students’ academic performance using stacking classifiers ensemble and synthetic minority over-sampling techniques. The research was conducted by adopting and evaluating the performance of J48, IBK and SMO classifiers. The individual classifiers models, standard stacking classifier ensemble model and stacking classifiers ensemble model were trained and tested on 206 students’ data set from the faculty of science federal university Dutse. Students’ specific previous academic performance records at Unified Tertiary Matriculation Examination, Senior Secondary Certificate Examination and first year Cumulative Grade Point Average of students are used as data inputs in WEKA 3.9.1 data mining tool to predict students’ graduation classes of degrees at undergraduate level. The result shows that application of synthetic minority over-sampling technique for class balancing improves all the various models performance with the proposed modified stacking classifiers ensemble model outperforming the various classifiers models in both performance accuracy and RSME values making it the best model.
Millennials and the use of social networking sites as a job searching tooljournalBEEI
This research is conducted to examine the factors that influence the behavioural intention of millienials in using SNS when seeking for a job. The data was collected from respondents who are from the generation Y demographic and actively looking for jobs. The respondents must possess some experience in using SNS when job hunting. The data was then gathered and analyzed using partial least square (PLS) which encompasses the measurement and structural models of the study. The findings revealed that three of the constructs as applied in TAM are statistically significant to behavioural intention. The three factors that influenced the job seekers’ intention to use SNSs as a job search tool are; perceived usefulness, perceived ease of use and privacy concerns. All these factors are elements which contribute to and have a significant relationship with job seekers’ intention to use SNSs, as verified using PLS data analysis. The recruiters or employers who intend to adopt SNSs in the recruitment process are advised to design the recruitment plan regarding the utilization of SNSs to be more convenient and user-friendly. This study provides insight and knowledge regarding the impact of technology in online job application and hiring processes.
Multiple educational data mining approaches to discover patterns in universit...IJICTJOURNAL
This paper presented the utilization of pattern discovery techniques by using multiple relationships and clustering educational data mining approaches to establish a knowledge base that will aid in the prediction of ideal college program selection and enrollment forecasting for incoming freshmen. Results show a significant level of accuracy in predicting college programs for students by mining two years of student college admission and graduation final grade scholastic records. The results of educational predictive data mining methods can be applied in improving the services of the admission department of an educational institution, particularly in its course alignment, student mentoring, admission forecast, marketing, and enrollment preparedness.
The International Journal of Information Technology, Control and Automation (...IJITCA Journal
The International Journal of Information Technology, Control and Automation (IJITCA) is a Quarterly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Information Technology (IT), Control Systems and Automation Engineering. The journal focuses on all technical and practical aspects of IT, Control Systems and Automation with applications in real-world engineering and scientific problems. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on information technology, control engineering, automation, modeling concepts and establishing new collaborations in these areas.
Authors are invited to contribute to this journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in Information Technology, Control Systems and Automation.
Information Technology Convergence Services & AI (ITCAI 2024)IJITCA Journal
Welcome to ITCAI 2024
** Registration is currently open **
Submit Your Research Articles...!!!
International Conference on Information Technology Convergence Services & AI (ITCAI 2024)
September 14 ~ 15, 2024, Virtual Conference
https://itca2024.org/
Submission Deadline : June 01, 2024
Contact us:
Here's where you can reach us : itca@itca2024.org or itcaiconf@gmail.com
Submission Link:
https://itca2024.org/submission/index.php
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The International Journal of Information Technology, Control and Automation (...IJITCA Journal
The International Journal of Information Technology, Control and Automation (IJITCA) is a Quarterly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Information Technology (IT), Control Systems and Automation Engineering. The journal focuses on all technical and practical aspects of IT, Control Systems and Automation with applications in real-world engineering and scientific problems. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on information technology, control engineering, automation, modeling concepts and establishing new collaborations in these areas.
Authors are invited to contribute to this journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in Information Technology, Control Systems and Automation.
The International Journal of Information Technology, Control and Automation (...IJITCA Journal
The International Journal of Information Technology, Control and Automation (IJITCA) is a Quarterly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Information Technology (IT), Control Systems and Automation Engineering. The journal focuses on all technical and practical aspects of IT, Control Systems and Automation with applications in real-world engineering and scientific problems. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on information technology, control engineering, automation, modeling concepts and establishing new collaborations in these areas.
Authors are invited to contribute to this journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in Information Technology, Control Systems and Automation.
The International Journal of Information Technology, Control and Automation (...IJITCA Journal
The International Journal of Information Technology, Control and Automation (IJITCA) is a Quarterly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Information Technology (IT), Control Systems and Automation Engineering. The journal focuses on all technical and practical aspects of IT, Control Systems and Automation with applications in real-world engineering and scientific problems. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on information technology, control engineering, automation, modeling concepts and establishing new collaborations in these areas.
Authors are invited to contribute to this journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in Information Technology, Control Systems and Automation.
The International Journal of Information Technology, Control and Automation (...IJITCA Journal
The International Journal of Information Technology, Control and Automation (IJITCA) is a Quarterly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Information Technology (IT), Control Systems and Automation Engineering. The journal focuses on all technical and practical aspects of IT, Control Systems and Automation with applications in real-world engineering and scientific problems. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on information technology, control engineering, automation, modeling concepts and establishing new collaborations in these areas.
Authors are invited to contribute to this journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in Information Technology, Control Systems and Automation.
The International Journal of Information Technology, Control and Automation (...IJITCA Journal
The International Journal of Information Technology, Control and Automation (IJITCA) is a Quarterly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Information Technology (IT), Control Systems and Automation Engineering. The journal focuses on all technical and practical aspects of IT, Control Systems and Automation with applications in real-world engineering and scientific problems. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on information technology, control engineering, automation, modeling concepts and establishing new collaborations in these areas.
Authors are invited to contribute to this journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in Information Technology, Control Systems and Automation.
The International Journal of Information Technology, Control and Automation (...IJITCA Journal
The International Journal of Information Technology, Control and Automation (IJITCA) is a Quarterly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Information Technology (IT), Control Systems and Automation Engineering. The journal focuses on all technical and practical aspects of IT, Control Systems and Automation with applications in real-world engineering and scientific problems. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on information technology, control engineering, automation, modeling concepts and establishing new collaborations in these areas.
Authors are invited to contribute to this journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in Information Technology, Control Systems and Automation.
The International Journal of Information Technology, Control and Automation (...IJITCA Journal
The International Journal of Information Technology, Control and Automation (IJITCA) is a Quarterly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Information Technology (IT), Control Systems and Automation Engineering. The journal focuses on all technical and practical aspects of IT, Control Systems and Automation with applications in real-world engineering and scientific problems. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on information technology, control engineering, automation, modeling concepts and establishing new collaborations in these areas.
Authors are invited to contribute to this journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in Information Technology, Control Systems and Automation.
2 nd International Conference on Soft Computing, Data mining and Data Scienc...IJITCA Journal
2
nd International Conference on Soft Computing, Data mining and Data Science (SCDD
2024) will provide an excellent international forum for sharing knowledge and results in
theory, methodology and applications of Soft Computing, Data mining, and Data Science.
The Conference looks for significant contributions to all major fields of the Soft Computing,
Data mining, and Data Science in theoretical and practical aspects. The aim of the
Conference is to provide a platform to the researchers and practitioners from both academia
as well as industry to meet and share cutting-edge development in the field.
Authors are solicited to contribute to the Conference by submitting articles that illustrate
research results, projects, surveying works and industrial experiences that describe significant
advances in the following areas, but are not limited to.
The International Journal of Information Technology, Control and Automation (...IJITCA Journal
The International Journal of Information Technology, Control and Automation (IJITCA) is a Quarterly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Information Technology (IT), Control Systems and Automation Engineering. The journal focuses on all technical and practical aspects of IT, Control Systems and Automation with applications in real-world engineering and scientific problems. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on information technology, control engineering, automation, modeling concepts and establishing new collaborations in these areas.
Authors are invited to contribute to this journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in Information Technology, Control Systems and Automation.
The International Journal of Information Technology, Control and Automation (...IJITCA Journal
The International Journal of Information Technology, Control and Automation (IJITCA) is a Quarterly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Information Technology (IT), Control Systems and Automation Engineering. The journal focuses on all technical and practical aspects of IT, Control Systems and Automation with applications in real-world engineering and scientific problems. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on information technology, control engineering, automation, modeling concepts and establishing new collaborations in these areas.
Authors are invited to contribute to this journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in Information Technology, Control Systems and Automation.
The International Journal of Information Technology, Control and Automation (...IJITCA Journal
The International Journal of Information Technology, Control and Automation (IJITCA) is a Quarterly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Information Technology (IT), Control Systems and Automation Engineering. The journal focuses on all technical and practical aspects of IT, Control Systems and Automation with applications in real-world engineering and scientific problems. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on information technology, control engineering, automation, modeling concepts and establishing new collaborations in these areas.
Authors are invited to contribute to this journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in Information Technology, Control Systems and Automation.
The International Journal of Information Technology, Control and Automation (...IJITCA Journal
The International Journal of Information Technology, Control and Automation (IJITCA) is a Quarterly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Information Technology (IT), Control Systems and Automation Engineering. The journal focuses on all technical and practical aspects of IT, Control Systems and Automation with applications in real-world engineering and scientific problems. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on information technology, control engineering, automation, modeling concepts and establishing new collaborations in these areas.
Authors are invited to contribute to this journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in Information Technology, Control Systems and Automation.
The International Journal of Information Technology, Control and Automation (...IJITCA Journal
The International Journal of Information Technology, Control and Automation (IJITCA) is a Quarterly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Information Technology (IT), Control Systems and Automation Engineering. The journal focuses on all technical and practical aspects of IT, Control Systems and Automation with applications in real-world engineering and scientific problems. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on information technology, control engineering, automation, modeling concepts and establishing new collaborations in these areas.
Authors are invited to contribute to this journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in Information Technology, Control Systems and Automation.
The International Journal of Information Technology, Control and Automation (...IJITCA Journal
The International Journal of Information Technology, Control and Automation (IJITCA) is a Quarterly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Information Technology (IT), Control Systems and Automation Engineering. The journal focuses on all technical and practical aspects of IT, Control Systems and Automation with applications in real-world engineering and scientific problems. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on information technology, control engineering, automation, modeling concepts and establishing new collaborations in these areas.
Authors are invited to contribute to this journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in Information Technology, Control Systems and Automation.
The International Journal of Information Technology, Control and Automation (...IJITCA Journal
The International Journal of Information Technology, Control and Automation (IJITCA) is a Quarterly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Information Technology (IT), Control Systems and Automation Engineering. The journal focuses on all technical and practical aspects of IT, Control Systems and Automation with applications in real-world engineering and scientific problems. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on information technology, control engineering, automation, modeling concepts and establishing new collaborations in these areas.
Authors are invited to contribute to this journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in Information Technology, Control Systems and Automation.
The International Journal of Information Technology, Control and Automation (...IJITCA Journal
The International Journal of Information Technology, Control and Automation (IJITCA) is a Quarterly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Information Technology (IT), Control Systems and Automation Engineering. The journal focuses on all technical and practical aspects of IT, Control Systems and Automation with applications in real-world engineering and scientific problems. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on information technology, control engineering, automation, modeling concepts and establishing new collaborations in these areas.
Authors are invited to contribute to this journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in Information Technology, Control Systems and Automation.
The International Journal of Information Technology, Control and Automation (...IJITCA Journal
The International Journal of Information Technology, Control and Automation (IJITCA) is a Quarterly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Information Technology (IT), Control Systems and Automation Engineering. The journal focuses on all technical and practical aspects of IT, Control Systems and Automation with applications in real-world engineering and scientific problems. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on information technology, control engineering, automation, modeling concepts and establishing new collaborations in these areas.
Authors are invited to contribute to this journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in Information Technology, Control Systems and Automation.
The International Journal of Information Technology, Control and Automation (...IJITCA Journal
The International Journal of Information Technology, Control and Automation (IJITCA) is a Quarterly open access peer-reviewed journal that publishes articles which contribute new results in all areas of Information Technology (IT), Control Systems and Automation Engineering. The journal focuses on all technical and practical aspects of IT, Control Systems and Automation with applications in real-world engineering and scientific problems. The goal of this journal is to bring together researchers and practitioners from academia and industry to focus on information technology, control engineering, automation, modeling concepts and establishing new collaborations in these areas.
Authors are invited to contribute to this journal by submitting articles that illustrate research results, projects, surveying works and industrial experiences that describe significant advances in Information Technology, Control Systems and Automation.
Read| The latest issue of The Challenger is here! We are thrilled to announce that our school paper has qualified for the NATIONAL SCHOOLS PRESS CONFERENCE (NSPC) 2024. Thank you for your unwavering support and trust. Dive into the stories that made us stand out!
Palestine last event orientationfvgnh .pptxRaedMohamed3
An EFL lesson about the current events in Palestine. It is intended to be for intermediate students who wish to increase their listening skills through a short lesson in power point.
Biological screening of herbal drugs: Introduction and Need for
Phyto-Pharmacological Screening, New Strategies for evaluating
Natural Products, In vitro evaluation techniques for Antioxidants, Antimicrobial and Anticancer drugs. In vivo evaluation techniques
for Anti-inflammatory, Antiulcer, Anticancer, Wound healing, Antidiabetic, Hepatoprotective, Cardio protective, Diuretics and
Antifertility, Toxicity studies as per OECD guidelines
Francesca Gottschalk - How can education support child empowerment.pptxEduSkills OECD
Francesca Gottschalk from the OECD’s Centre for Educational Research and Innovation presents at the Ask an Expert Webinar: How can education support child empowerment?
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
Acetabularia Information For Class 9 .docxvaibhavrinwa19
Acetabularia acetabulum is a single-celled green alga that in its vegetative state is morphologically differentiated into a basal rhizoid and an axially elongated stalk, which bears whorls of branching hairs. The single diploid nucleus resides in the rhizoid.
Embracing GenAI - A Strategic ImperativePeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
Synthetic Fiber Construction in lab .pptxPavel ( NSTU)
Synthetic fiber production is a fascinating and complex field that blends chemistry, engineering, and environmental science. By understanding these aspects, students can gain a comprehensive view of synthetic fiber production, its impact on society and the environment, and the potential for future innovations. Synthetic fibers play a crucial role in modern society, impacting various aspects of daily life, industry, and the environment. ynthetic fibers are integral to modern life, offering a range of benefits from cost-effectiveness and versatility to innovative applications and performance characteristics. While they pose environmental challenges, ongoing research and development aim to create more sustainable and eco-friendly alternatives. Understanding the importance of synthetic fibers helps in appreciating their role in the economy, industry, and daily life, while also emphasizing the need for sustainable practices and innovation.
Adversarial Attention Modeling for Multi-dimensional Emotion Regression.pdf
MINING DISCIPLINARY RECORDS OF STUDENT WELFARE AND FORMATION OFFICE: AN EXPLORATORY STUDY TO ENHANCE THE UNIVERSITY SERVICES PORTFOLIO
1. International Journal of Information Technology, Control and Automation (IJITCA) Vol. 7, No.2, April 2017
DOI:10.5121/ijitca.2017.7202 23
MINING DISCIPLINARY RECORDS OF STUDENT
WELFARE AND FORMATION OFFICE:
AN EXPLORATORY STUDY TO ENHANCE THE
UNIVERSITY SERVICES PORTFOLIO
Paulino H. Gatpandan , Shaneth C. Ambat
School of Graduate Studies, AMA University, Quezon City, Philippines
ABSTRACT
Data mining is the process of analyzing large datasets, understanding their patterns and discovering useful
information from a large amount of data. Decision tree as one of the common algorithm of data mining is a
tree structure entailing of internal and terminal nodes which process the data to eventually produce a
classification. Classification is the process of dividing a dataset together in a high-class set such that the
members of each set are nearby as expected to one another, and different groups are as far as expected
from one another, where distance is measured with respect to the specific variable(s) you are trying to
predict. Data Envelopment Analysis is a technique wherein the productivity of a unit is evaluated by
equating the volume/amount of output(s) in relation to the volume/amount of input(s) used. The
performance of a unit is calculated by equating its efficiency with the best-perceived performance in the
data set. In this study, a model for measuring the efficiency of Decision Making Units will be presented,
along with related methods of implementation and interpretation. DEA assesses and evaluates the
efficiency of a unit dubbed as Decision-Making Units or DMU. There are many classification techniques
and algorithms but the research study used decision tree using CHAID algorithms. Classification decision
tree algorithm using CHAID as data mining technique identifies the relationship between the demographic
profile of the students and the category of offenses. Cross tabulation is a tool used to analyze categorical
data. It is a type of table in a matrix format that shows the multivariate occurrence dissemination of the
variables and delivers a basic picture of the interrelation between two variables. Both CHAID algorithm
and cross tabulation obtained the same results implying that higher percentage of students commit minor
offenses regardless of college, gender, year level, month and course. The CHAID algorithm used in a
software application Student Offenses Remediation System (STORES) serves as remediation plan for the
university. Further studies should be conducted to identify the effectiveness of the remediation plan by
conducting an empirical investigation on the rule set and/or implement another algorithm to determine the
program efficiency.
KEYWORDS
Data Mining, Classification, Decision Tree, CHAID Algorithm, Data Envelopment Analysis
1. INTRODUCTION
Data mining is the process of analyzing large datasets, understanding their patterns [1] and
discovering useful information from a large amount of data [2]. The common data mining
algorithms include a) decision tree method, b) bionic global optimized genetic algorithm and
neural network, c) statistical analysis and reports of the exclusive counter example method,
among others.
The decision tree is a tree structure entailing of internal and terminal nodes which process the
data to eventually produce a classification. The decision tree is capable of preserving the role of
dimensionality reduction and at establishing an optimum size classification.
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Classification is one of the most common applications for data mining. Classification is the
process of dividing a dataset together in high-class sets such that the members of each set are
nearby as expected to one another, and different groups are as far as expected from one another,
where distance is measured with respect to the specific variable(s) you are trying to predict.
Data Envelopment Analysis is a state of the art benchmarking method which is of great value for
multi-criteria benchmarking studies. Efficiency is the ratio between the outputs produced with the
number of inputs used. In the Handbook of data envelopment analysis of [3] data envelopment
analysis is a data-oriented approach for assessing and evaluating the performance of a set of peer
objects called Decision Making Units (DMUs), which transform multiple inputs into multiple
outputs. In most recent researches, DEA was used in evaluating the performances of different
kinds of entities engaged in different activities such as hospitals, cities, courts, universities,
business firms, and others. Several scholarly works used the DEA as measuring efficiency
performance of an organization.
Every university maintains academic enablers to emphasize the motivational and cognitive
factors for student academic success. In other universities, the academic affairs and student
affairs was combined into one reporting unit because of the twofold strengths, it enables student
affairs personnel to become familiar with the priorities of the academic division, and it allows
them to develop closer relationships with faculty in order to more effectively help students to
learn in a holistic and coordinated manner [4].
The Student Welfare and Formation Office (SWAFO) is an entity responsible of carrying out of
student discipline policies, rules and code of practice as specified in the Student Handbook. The
office is currently facing in a volume of students committing an offense from different colleges.
In this study, DEA will be used to assess the efficiency of the seven (7) colleges to determine the
most efficient college which will serve as a benchmark for the inefficient colleges. One of the
variables to be considered to determine the efficiency of a certain college is the minimal number
of students who commit offenses.
2. LITERATURE REVIEW
Charnes, Cooper, Lewin & Seiford [5] introduced Data Envelopment Analysis in their work data
envelopment analysis theory. DEA has been used for measuring and assessing the relative
performances of a set of organizations called DMUs which use a variety of inputs to produce a
variation of common output.
Several scholarly works have been identified and done in measuring the efficiency in different
fields such as banking industry, education institutions, farming and agricultures, crimes among
many others using data envelopment analysis.
Walraven, Koning, Bijmolt & Los [6] proposed data envelopment analysis as a method for
benchmarking sponsorship efficiency and demonstrate its effectiveness by applying it to a sample
of seventy-two (72) major Dutch sports sponsorship projects. Baran, Wysokinski, Stas,
Samolejova & Lenort used DEA model to identify the metallurgical efficiency such as overall
technical efficiency, pure technical efficiency and scale efficiency of branches in Poland.
Dzemydaite, Dzemyda, & Galiniene [8] measured the efficiency level of innovation systems by
applying a nonparametric DEA in Eastern and Central Europe. Tran Thi Thu & Bhaiyat [9]
measured the technical and scale efficiency of Vietnamese Commercial banks using a
nonparametric DEA. CCR model was applied to measure the overall technical efficiency. BCC
model was applied to evaluate the managerial skills. Duguleaña & Duguleaña [10] used DEA to
determine the technical efficiency of academic departments at Transylvania University during the
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academic year 2014 – 2015. The results of DEA model was used as a basis for improving the
efficiency of academic departments. Kashim, Kashim, Nadhar Khan, Rahim, & Hassan [11]
suggested the best framework for measuring the productivity in Higher Learning Institutions
(HLI). Data Envelopment Analysis model was used to analyze efficiency, effectiveness, and
productivity of the Higher Learning Institutions. Malhotra, Poteau, & Fritz [12] compared the
DMUs organizations’ performance of thirteen thrifts and mortgage finance companies for the
year 2008 to 2011 to evaluate the relative efficiency of the firms in terms of financial strengths.
Luna, Gil-Garcia, Luna-Reyes, Sandoval-Almazan, & Duarte-Valle [13] proposed a study that
assesses the efficiency performance of electronic portals to fully understand the factors that
influence the quality of the information and services provided to businesses, citizens and other
stakeholders. The study used DEA to calculate how the government’s efficiency in terms of
inputs to produce high-quality e-government portals. Dobrea, Ciocoiu, & Dinu [14] applied an
output oriented BCC DEA model to measure the sustainable and balanced development in the
investment of the regional efficiencies in the 42 countries panel data from the year 2005 to 2010.
Dočekalova, & Bočkova [15] utilized the application of the DEA on Research and Development
(R&D) to measure the effectiveness of Czech manufacturing industry. Elshamy [16] utilized
DEA to investigate and estimate the technical efficiency of Egyptian manufacturing sector.
Vierstraete [17] used a nonparametric DEA method to assess the three factors that measure the
health, education, and standard of living of the population. Estrada, Song, Kim, Namn, Kang [18]
developed a method of stepwise benchmarking for inefficient DMUs based on proximity-based
target selection. DEA was used to determine the efficiency score of DMU. Adams [19] computed
and evaluate the technical efficiency of public school districts in the State of Arkansas using an
output oriented variable returns to scale data envelopment analysis.
Hou, Guthrie, & Rigby [20] theorized that remediation has grown up from developing notions
into an extensively accepted new institutional custom to comprise of an activity correct shortages,
and include a process for outlining deficiencies and providing resources for improvement towards
acceptable performance [21]. The remediation plan is a valuable learning tool that refers to a
process of providing planned course of actions in correcting the deficiency or an act of offering
improvements. A study using a remediation plan were identified in the scholarly works of [22]
[23] [24] and [21]. Mee & Schreiner [22] summarized key findings of the literature about
remediation strategies used in nursing programs and policies that impact the student outcomes.
Gajewski, & Mather [23] presented an overview of a course-based remediation model developed
to enhance student learning in order to increase the rate of student retention. Makhani, Bradley,
Wong, Krynski, Jarvis, & Szumacher [24] reviewed remediation in allied health and professional
programs. Remediation requires multiple assessors and several assessment tools, feedback and
reassessment, and proactive involvement in supporting the identified students. Wu, Siewert, &
Boiselle [21] developed a multifaceted approach to early identification and prompt remediation of
difficulties to resident evaluation. The study designed a comprehensive remediation program
which used resources within radiology department.
A decision tree is a data mining technique for presenting the classifiers and regressions model. It
consists of some nodes and branches. In the classifying decision tree, the leaves specify classes.
Decision tree describes all content alone independent of an expert to interpret the output. The
graph method may be simpler than other classifying methods due to explanation and analysis. On
the other hand, big numbers of nodes may create decision tree graphic representation as harder.
Several scholarly works were identified using a classification data mining technique. Abbaszadeh
Afshar, Ayoubi, Besalatpour, Khademi, & Castrignano [25] estimated the soil clay content in two
depths using the geophysical technique (Ground Penetration Radar and Electromagnetic
induction) and ancillary variables (remote sensing and topographic data) in an arid region in
Southeastern Iran. CHAID model showed greater potential in predicting soil clay content from
geophysical and ancillary data while traditional regression model did not perform as well.
Eyduran, Keskin, Erturk, Dag, Tatliyer, Tirink, & Tariq [26] used CHAID algorithm to obtain a
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more flexible prediction of fleece weight from some physical wool characteristics of sheep which
provides a tree-based decision. Kurt, Duru, Canbay, & Duru. [27] applied a classification data
mining to predict the magnetic susceptible of the soil. Jimenez-Perez, & Mora-Lopez [28]
applied and utilized a two data mining techniques using clustering and classification techniques
for the predicting hourly values of global radiation for the next day. Mistikoglu, Gerek, Erdis,
Mumtaz Usmen, Cakan, & Kazan [29] demonstrated the utility of decision tree method in fall
accidents experienced by roofers. Algorithms such as C5.0 and CHAID were used in the study to
produce decision trees and to mine rules that demonstrate the associations among the input and
output variables for roofer fall accidents. Zhang, Fu, Peng, & Li [30] investigated the
classification of developing and non-developing tropical disturbances in the Western North
Pacific of a decision tree using a C4.5 algorithm. Althuwaynee, Pradhan, Park, & Lee [31] used
CHAID method to perform the best classification fit for each conditioning factors and combined
it with logistic regression to find the corresponding coefficient of best fitting function. The study
showed the efficacy and consistency of the collaboration DT and LR model in conquest
vulnerability plotting. Miller, Fridline, Pei-Yang, & Marino [32] generated a model for the early
detection of Metabolic Syndrome (MetS) in young adults. The model was derived using CHAID
decision tree analysis with waist circumference user-specified to detect MetS in young adults
using records of the National Health and Nutrition Examination Survey (NHANES) year 2009-
2010. Cho & Kurup [33] utilized a decision tree approach using two different tree models such as
C4.5 and CART for the classification and dimensionality reduction of Electronic Nose (EN).
Kaur, Singh, Garg & Harmanpreet [34] studied about classification algorithm for farm Decision
Support System. Several classification algorithms used are limited search, ID3, CHAID, C4.5,
improved C4.5 and One VS all decision tree and applied to one common data set of the crop with
specified class.
3. METHODOLOGY
The study is a quantitative method of research that uses the statistical method to quantify and
analyze the data to generalize results from a sample population. It appears the discussion in
tables containing data in the form of numbers and statistics. During the development of the
remediation plan, the proponent will use the framework for remediation plan phases.
3.1. RESEARCH DESIGN
Data Envelopment Analysis is a technique wherein the productivity of a unit is evaluated by
equating the volume/amount of output(s) in relation to the volume/amount of input(s) used. The
performance of a unit is calculated by equating its efficiency with the best-perceived performance
in the data set. In this study, a model for efficiency measurement of Decision Making Units will
be showed, along with related methods of implementation and interpretation. DEA assesses and
evaluates the efficiency of a unit dubbed as Decision Making Units or DMUs using the
illustrations below:
Eq. (1)
There are several classification techniques and algorithms but the research study used decision
tree using CHAID algorithms. In the scholarly works of [32], decision tree analysis can visualize
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the relationship pathways between the binary object variable and the associated uninterrupted
and/or categorical predictor variables with a tree image.
Other scholarly works of [31] stated that Multivariate statistical CHAID method is a tree that has
branches which represent the predictors and discriminate sample groups that produced an
estimated significant chi-square level of interaction.
The proponents opted to use classification decision tree algorithm using CHAID as data mining
technique to identify the relationship between the demographic profile of the students and the
category of offenses. The methodology that the proponents used for the Remediation Plan
process is shown below.
Figure 1.0 Remediation Plan Process
The process is divided into three (3) phases namely: identify, analyze, and mitigate.
Identification phase involves gathers pertinent information of students’ profile, offenses
committed, and complaints. Alerts will be identified based on the number of recurring offenses.
Analysis phase involves set of rules or algorithm using the demographic method to filter and
extracts data profiling and classify results. The mitigation phase responds and remediates a
planned course of action as a student remediation program.
The use of efficient, effective, and precise remediation plan techniques is very important for a
system to provide a useful course plan of actions such as a student remediation program.
Figure 2.0 Remediation Process Diagram
Demographic Filtering techniques classify the information into a demographic category based on
student profile details and offense category.
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DMUs Inputs Output
Budget
Personnel
Radio
Computer
Laptop
Average Population
Number of Students with Offenses
CSCS, CLAC, CTHM,
COEd, CCJE,
CEAT, CBAA
Number of Students without
Offenses
Technical Scale Technical Scale Technical Scale
Efficiency Efficiency Efficiency Efficiency Efficiency Efficiency
Score Score Score Score Score Score
CSCS 0.92 0.92 1.00 1.00 0.81 1.00 0.94 2
CLAC 1.00 1.00 0.87 0.87 1.00 0.87 0.93 3
CTHM 0.75 0.75 0.69 0.69 0.72 0.69 0.71 6
COEd 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1
CCJE 1.00 1.00 0.87 0.87 0.77 0.87 0.89 5
CEAT 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1
CBAA 0.97 0.97 0.89 0.89 0.93 0.89 0.92 4
2013
DMU
2014 2015
RankingAverage
3.2 OTHER TOOLS USED IN THE RESEARCH STUDY
MaxDEA software was used to obtain measures of productivity and efficiency to conduct data
envelopment analysis.
SPSS was used to generate the decision tree for classification model using CHAID algorithm.
Microsoft.net 4.5 was used as the environment framework, Visual Studio 2013 as the integrated
development environment, Visual C# as programming language, ASP.NET mv5 as development
framework for single page application in the web-based environment, SQL Server 2012 for data
store/persistence, Internet Information Services as the web server, jQuery 1.10 for JavaScript
framework, jQuery EasyUI for front-end user interface framework, DotNet.Highcharts for
charting and visualization, Entity Framework 6 for domain entities/models and Dapper Micro-
ORM for access.
4. RESULTS AND DISCUSSION
The efficient colleges were determined through Data Envelopment Analysis. The proponents used
the model of Radial Measure of Efficiency using an input-oriented orientation and a Rate-to-
Scale (RTS) using Scale efficiency. The proponents also used another model to test the
efficiency of the colleges such as Charnes, Cooper, and Rhodes (CCR) model using input-
oriented and output-oriented and Hybrid Measure of Efficiency model and NonRadial Measure of
Efficiency model using an input-oriented orientation and a Rate-to-Scale (RTS) using constant
returns to scale (CRS). The three models mentioned obtained the same results.
Table 1.0 : The variables used in determining the efficient and inefficient Colleges
Table 1.0 presents the seven (7) colleges as Decision-Making Units (DMUs), inputs such as
budget, personnel, radio, computer, laptop, average population, the number of students with
offenses, and the output which is the number of students without an offense.
Table 2.0 : 3 Years Scale Efficiency Results of the Seven (7) Colleges
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School Year
1st
Semester
2nd
Semester
Average
Population
Students with
Violation
Percentage
2012 - 2013 12,864 11,936 12400 6921 55.81%
2013 - 2014 13,208 12,301 12755 5236 41.05%
2014 - 2015 13,744 12,977 13361 6065 45.40%
Cases
Valid Missing Total
N Percent N Percent N Percent
College * Category_Offense 6065 100.0% 0 0.0% 6065 100.0%
Gender * Category_Offense 6065 100.0% 0 0.0% 6065 100.0%
Year_Level *
Category_Offense
6065 100.0% 0 0.0% 6065 100.0%
Course * Category_Offense 6065 100.0% 0 0.0% 6065 100.0%
Month * Category_Offense 6065 100.0% 0 0.0% 6065 100.0%
Table 2.0 presents the 3-year Scale Efficiency Results of the seven (7) colleges. CTHM got an
average efficiency score of 0.71 and ranked 6th being the lowest among all colleges. CCJE got an
average efficiency score of 0.89 and ranked 5th inefficient DMU. CBAA got an average
efficiency score of 0.92 and ranked 4th inefficient DMU. CLAC got an average efficiency score
of 0.93 and ranked 3rd inefficient DMU. CSCS got an average efficiency score of 0.94 and
ranked 2nd inefficient DMU. COEd and CEAT got an average efficiency score of 1.00 for three
(3) years and ranked 1st being the efficient DMU. COEd and CEAT was determined as the
efficient DMUs due to less number of students without and offense in relation to average
population.
Table 3.0 : Average Population, Students with Violation and Percentage of Students with Violation for 3
years
Table 3.0 presents the average population, number of students with violation and percentage of
students with the violation. SY 2012-2013 has 6921 students with violation equivalent to 55.81%.
SY 2013-2014 has 5236 students with violation equivalent to 41.05%. SY 2014-2015 has 6065
students with violation equivalent to 45.40%.
4.1 CROSS TABULATION
Cross tabulation is a tool used to analyze categorical data. It is a type of table in the matrix format
that shows the multivariate occurrence dissemination of the variables and delivers a basic picture
of the interrelation between two variables.
Table 4.0 : Case Processing Summary
Table 4.0 presents the case processing summary. The result of cross tabulation shows 100% valid
data and 0% missing data.
4.2 CHAID ALGORITHM
The CHAID (Chi Square Automatic Interaction Detection) is a form of analysis that delineates
how variables best combine to explain the outcome in a given dependent variable. CHAID
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analysis builds a predictive model, or tree, to help define how variables best unify to describe the
outcome in the given dependent variable. CHAID generates all potential cross tabulations for
each predictor category until the greatest result is attained and no further splitting can be
accomplished.
Figure 3.0 Decision Tree using CHAID Algorithm
CHAID Rule Set
/* Node 1 */.
IF (Month = "April")
THEN
Node = 1
Prediction = 4
Probability = 0.888608
/* Node 2 */.
IF (Month != "April" AND Month != "May" AND Month != "Dec" AND Month != "Nov"
AND Month != "Oct" AND Month != "August" AND Month != "June" AND Month !=
"March" AND Month != "Sept" AND Month != "Jan")
THEN
Node = 2
Prediction = 4
Probability = 0.964831
/* Node 16 */.
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IF (Month = "May") AND ((Age <= 17)) AND (Gender = "Female")
THEN
Node = 16
Prediction = 4
Probability = 0.686747
/* Node 17 */.
IF (Month = "May") AND ( (Age <= 17)) AND (Gender != "Female")
THEN
Node = 17
Prediction = 4
Probability = 0.849057
/* Node 8 */.
IF (Month = "May") AND (Age > 17))
THEN
Node = 8
Prediction = 4
Probability = 0.946578
/* Node 18 */.
IF (Month = "Dec" OR Month = "March") AND (Year_Level = "Fourth Year" OR Year_Level
= "Second Year") AND (College != "CLAC" AND College != "CSCS" AND College !=
"CTHM")
THEN
Node = 18
Prediction = 4
Probability = 0.980000
/* Node 19 */.
IF (Month = "Dec" OR Month = "March") AND (Year_Level = "Fourth Year" OR Year_Level
= "Second Year") AND (College = "CLAC" OR College = "CSCS" OR College = "CTHM")
THEN
Node = 19
Prediction = 4
Probability = 0.900943
/* Node 10 */.
IF (Month = "Dec" OR Month = "March") AND (Year_Level = "Third Year")
THEN
Node = 10
Prediction = 4
Probability = 0.907801
/* Node 11 */.
IF (Month = "Dec" OR Month = "March") AND (Year_Level != "Fourth Year" AND
Year_Level != "Third Year" AND Year_Level != "Second Year")
THEN
Node = 11
Prediction = 4
Probability = 0.973684
/* Node 12 */.
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IF (Month = "Nov" OR Month = "August" OR Month = "Sept") AND (Age NOT MISSING
AND (Age <= 17))
THEN
Node = 12
Prediction = 4
Probability = 0.905759
/* Node 20 */.
IF (Month = "Nov" OR Month = "August" OR Month = "Sept") AND (Age IS MISSING OR
(Age > 17)) AND (College != "CEAT" AND College != "COED")
THEN
Node = 20
Prediction = 4
Probability = 0.784119
/* Node 21 */.
IF (Month = "Nov" OR Month = "August" OR Month = "Sept") AND (Age IS MISSING OR
(Age > 17)) AND (College = "CEAT" OR College = "COED")
THEN
Node = 21
Prediction = 4
Probability = 0.928000
/* Node 14 */.
IF (Month = "Oct" OR Month = "June" OR Month = "Jan") AND (Year_Level = "Fourth Year"
OR Year_Level = "Third Year")
THEN
Node = 14
Prediction = 4
Probability = 0.824701
/* Node 15 */.
IF (Month = "Oct" OR Month = "June" OR Month = "Jan") AND (Year_Level != "Fourth Year"
AND Year_Level != "Third Year")
THEN
Node = 15
Prediction = 4
Probability = 0.914661
Based on the rule set of CHAID algorithm using category offense as the dependent variable,
prediction of node 1 is 4 referring to minor offense with a probability of 0.89; prediction of node
2 is 4 referring to minor offense with a probability of 0.96; prediction of node 16 is 4 referring to
minor offense with a probability of 0.69; prediction of node 17 is 4 referring to minor offense
with a probability of 0.85; prediction of node 8 is 4 referring to minor offense with a probability
of 0.95; prediction of node 18 is 4 referring to minor offense with a probability of 0.98; prediction
of node 19 is 4 referring to minor offense with a probability of 0.90; prediction of node 10 is 4
referring to minor offense with a probability of 0.91; prediction of node 11 is 4 referring to minor
offense with a probability of 0.97; prediction of node 12 is 4 referring to minor offense with a
probability of 0.91; prediction of node 20 is 4 referring to minor offense with a probability of
0.78; prediction of node 21 is 4 referring to minor offense with a probability of 0.93; prediction of
node 14 is 4 referring to minor offense with a probability of 0.82; and prediction of node 15 is 4
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referring to minor offense with a probability of 0.91. All the nodes have a prediction value of 4
referring to the minor offense. Both CHAID algorithm and cross tabulation obtained the same
results implying that higher percentage of students commit minor offenses regardless of college,
gender, year level, month and course.
4.3 REMEDIATION PLAN: STUDENT OFFENSES REMEDIATION SYSTEM (STORES)
The CHAID algorithm has been implemented in the software application for Student Offenses
Remediation System (StOReS). The following figures are the sample screen shots of the system.
Figure 4.0 Login Page
Figure 4.0 shows the Login Page of the system. Registered users are asked for authentication
thus entering a username and password for access.
Figure 5.0 Complaint Facility
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Figure 5.0 shows the Complaint Facility of the system. Once the student commits an offense, this
module serves as a data entry about student information and the committed offenses. The system
automatically detects the category of the offense and its equivalent sanctions. The system also
determines the remediation to be given to the student.
Figure 6.0 Dashboard
Figure 6.0 shows the Dashboard of the system which presents the summary of the offenses
committed by gender, course, college, and offense category.
Figure 7.0 Data Analytics and Report Visualization – By College
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Figure 7.0 shows a detailed report visualization of the system which presents the offenses
committed by college.
Figure 8.0 Data Analytics and Report Visualization – By Offense Category
Figure 8.0 shows a detailed report visualization of the system which presents the offenses
committed by offense category.
Figure 9.0 Data Analytics and Report Visualization – By College per Course
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Figure 9.0 shows a detailed report visualization of the system which presents the offenses
committed by college per course.
5. CONCLUSION
The purpose of the study is to conduct mining on disciplinary records of students to determine the
pattern of their offenses using CHAID algorithm and cross tabulation. Based on the pattern
derived, a remediation plan was developed to help the seven (7) colleges to lessen the number of
student offenses. DEA was used to determine the efficiency of the seven (7) colleges that served
as DMUs. The DMUs that has lesser number of students with the offense was determined
efficient DMUs, hence efficient DMUs served as a model to inefficient DMUs to lessen the
number of student offenses. Based on the three 3-year historical data, two (2) colleges was
determined as efficient DMUs identifiably, the COEd and CEAT. The CHAID Algorithm was
implemented in a software application for Student Offenses Remediation System (StOReS) which
is the proponents recommended remediation plan for the university. The proponents highly
recommend that the remediation plan should be implemented in the university. Further studies
should be conducted to identify the effectiveness of the remediation plan by conducting an
empirical investigation on the rule set and or implement other algorithms to determine the
program efficiency.
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Authors
MR. PAULINO H. GATPANDAN is pursuing his degree of Doctor in
Information Technology at AMA Computer University and currently writing
his dissertation. He is a Master in Business Administration degree holder from
Philippine Christian University-Dasmariñas, and a Master of Science in
Computer Science degree holder from AMA Computer University-Makati. He
completed his academic baccalaureate degree of Bachelor of Science in
Computer Science from the Philippine Christian University-Dasmariñas,
Cavite. He is a fulltime faculty of Computer Studies Department at De La Salle
University-Dasmariñas. He has been in the academe in the teaching profession
for 17 years. He is well-versed in Database Management leading to an IBM
Certified Designer-Cognos 10 BI Reports, and IBM Academic Associate DB2-
certified.
DR. SHANETH C. AMBAT received her Doctor of Philosophy in
Engineering major in Information Technology in Hannam University, South
Korea in 2009. She received her Bachelor of Science in Computer Science in
1995 and Master of Science in Computer Science in 2004 respectively at AMA
Computer University, Makati City. She is currently the Dean of the School of
Graduate Studies at AMA Computer University, Quezon City. Her research
interest includes data envelopment analysis, data mining, SOM, reinforcement
learning algorithm, and fuzzy logic.