Prediction of students academic achievement in UniMAP using data mining approach

The main objective of this research is to predict the academic achievement of the students in UniMAP who will be succeed, will be continued their study in higher level and also students whose need help in their study. Besides that, the specific objectives of this research are to identify the fact...

Full description

Saved in:

Bibliographic Details
Format:	Thesis
Language:	English
Subjects:	Data mining Educational Data Mining (EDM)
Online Access:	http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/77203/1/Page%201-24.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/77203/2/Full%20text.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/77203/4/Fatihah%20Aziz.pdf
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my-unimap-77203
record_format	uketd_dc
spelling	my-unimap-772032022-11-25T01:24:39Z Prediction of students academic achievement in UniMAP using data mining approach Abdul Wahab, Jusoh, Assoc. Prof. Dr. The main objective of this research is to predict the academic achievement of the students in UniMAP who will be succeed, will be continued their study in higher level and also students whose need help in their study. Besides that, the specific objectives of this research are to identify the factors which influence the academic achievement of the students, to develop the decision tree model for prediction of the academic achievement of the students and lastly, to evaluate the performance of the decision tree model. Our research methodology started with the collection of students’ data from UniMAP since 2002 until 2012. Then, continued with the implementation of the decision tree model by using the C4.5 algorithm to develop the model for predicting the students’ academic achievement in UniMAP. C4.5 algorithm is a successor of ID3 algorithm which had been invented by J.R Quilan in 1986. In this research, JMP Pro 11 software has been used in developed the decision tree model. In addition, the finding of this research stated that there were five factor variables had influenced the academic achievement of the students in UniMAP. The factor variables were gender, age, entry qualification, entry CGPA and results from semester 1 and 2. The response variable was the result of graduate students. Moreover, from the result of the decision tree, the knowledge representation has been interpreted into decision rules using IF-THEN rules. From the predictive model, there were 25 decision rules which had interpreted. Later, the rules had been implemented into a simple academic prediction system for the students in UniMAP. This simple prediction system could help new students to predict their final result in the earlier semester. Some of the significant finding from this research, found that students who in between 24 to 30 years old had graduated with excellent result than younger and older adult learners. Female students from this university had graduated with more excellent result than the male students. Lastly, the finding of this research found that students who entry the university with the Matriculation qualification graduated with more excellent result than Diploma and STPM. Universiti Malaysia Perlis (UniMAP) Thesis en http://dspace.unimap.edu.my:80/xmlui/handle/123456789/77203 http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/77203/3/license.txt 8a4605be74aa9ea9d79846c1fba20a33 http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/77203/1/Page%201-24.pdf 7b80ecec39f55f6cb864c9e36645943a http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/77203/2/Full%20text.pdf bb25f6403a5982b413a6c1fa7371a837 http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/77203/4/Fatihah%20Aziz.pdf eadd4679a742b2190a4c919cfdf19702 Universiti Malaysia Perlis (UniMAP) Data mining Educational Data Mining (EDM) Institute of Engineering Mathematics
institution	Universiti Malaysia Perlis
collection	UniMAP Institutional Repository
language	English
advisor	Abdul Wahab, Jusoh, Assoc. Prof. Dr.
topic	Data mining Educational Data Mining (EDM)
spellingShingle	Data mining Educational Data Mining (EDM) Prediction of students academic achievement in UniMAP using data mining approach
description	The main objective of this research is to predict the academic achievement of the students in UniMAP who will be succeed, will be continued their study in higher level and also students whose need help in their study. Besides that, the specific objectives of this research are to identify the factors which influence the academic achievement of the students, to develop the decision tree model for prediction of the academic achievement of the students and lastly, to evaluate the performance of the decision tree model. Our research methodology started with the collection of students’ data from UniMAP since 2002 until 2012. Then, continued with the implementation of the decision tree model by using the C4.5 algorithm to develop the model for predicting the students’ academic achievement in UniMAP. C4.5 algorithm is a successor of ID3 algorithm which had been invented by J.R Quilan in 1986. In this research, JMP Pro 11 software has been used in developed the decision tree model. In addition, the finding of this research stated that there were five factor variables had influenced the academic achievement of the students in UniMAP. The factor variables were gender, age, entry qualification, entry CGPA and results from semester 1 and 2. The response variable was the result of graduate students. Moreover, from the result of the decision tree, the knowledge representation has been interpreted into decision rules using IF-THEN rules. From the predictive model, there were 25 decision rules which had interpreted. Later, the rules had been implemented into a simple academic prediction system for the students in UniMAP. This simple prediction system could help new students to predict their final result in the earlier semester. Some of the significant finding from this research, found that students who in between 24 to 30 years old had graduated with excellent result than younger and older adult learners. Female students from this university had graduated with more excellent result than the male students. Lastly, the finding of this research found that students who entry the university with the Matriculation qualification graduated with more excellent result than Diploma and STPM.
format	Thesis
title	Prediction of students academic achievement in UniMAP using data mining approach
title_short	Prediction of students academic achievement in UniMAP using data mining approach
title_full	Prediction of students academic achievement in UniMAP using data mining approach
title_fullStr	Prediction of students academic achievement in UniMAP using data mining approach
title_full_unstemmed	Prediction of students academic achievement in UniMAP using data mining approach
title_sort	prediction of students academic achievement in unimap using data mining approach
granting_institution	Universiti Malaysia Perlis (UniMAP)
granting_department	Institute of Engineering Mathematics
url	http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/77203/1/Page%201-24.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/77203/2/Full%20text.pdf http://dspace.unimap.edu.my:80/xmlui/bitstream/123456789/77203/4/Fatihah%20Aziz.pdf
_version_	1776104249754648576

Prediction of students academic achievement in UniMAP using data mining approach

Similar Items