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...
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| Format: | Thesis |
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| Language: | English |
| Subjects: | |
| 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 |
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| Summary: | 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. |
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