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Journal of Computer Science and Information Technology
Abstract
The desire of every organization is to extract hidden but useful knowledge from
their data through data mining tools. Also, the recent decline in the standard of
education in most developing countries has necessitated researches that will help
proffer solutions to some of the problems. From the literature, different analysis has
been carried out on university data, which includes student’s university entrance
examination and Ordinary level results but the relationship between these entry
results and students’ final graduation grades has been in isolation. Therefore, in this
work, a new system that will predict students’ graduation grades based on entry
results data using the Iterative Dichotomiser 3 (ID3) decision tree algorithm was
developed. ID3 decision tree algorithm was used to train the data of the graduated
sets. The knowledge represented by decision trees were extracted and presented in
form of IF-THEN rules. The trained data were then used to develop a model for
making future prediction of students’ graduation grades. The developed system
could be very useful in predicting students’ final graduation grades even from the
point of entry into the university. This will help management staff, academic
planners to properly counsel students in order to improve their overall performance.
Keywords: Data mining, Decision trees, Prediction, ID3 algorithm, Knowledge
extraction
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Citation
33. Ogunde A. O. and Ajibade D. A. (2014). A Data Mining System for Predicting University Students’ Graduation Grades Using ID3 Decision Tree Algorithm. Journal of Computer Science and Information Technology, Volume 2, Issue 1, Pg 21-46. Published by American Research Institute for Policy Development, USA.
