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Published in:   Vol. 5 Issue 1 Date of Publication:   June 2016

Perfomance Comparison of Decsion Tree Algorithms to Findout the Reason for Student�s Absenteeism at the Undergraduate Level in a College for an Academic Year

G. Suresh,K. Arunmozhi Arasan, S. Muthukumaran

Page(s):   16-21 ISSN:   2278-2397
DOI:   10.20894/IJBI.105.005.001.005 Publisher:   Integrated Intelligent Research (IIR)

Educational data mining is used to study the data available in the educational field and bring out the hidden knowledge from it. Classification methods like decision trees, rule mining can be applied on the educational data for predicting the students behavior. This paper focuses on finding thesuitablealgorithm which yields the best result to find out the reason behind students absenteeism in an academic year. The first step in this processis to gather students data by using questionnaire.The datais collected from 123 under graduate students from a private college which is situated in a semirural area. The second step is to clean the data which is appropriate for mining purpose and choose the relevant attributes. In the final step, three different Decision tree induction algorithms namely, ID3(Iterative Dichotomiser), C4.5 and CART(Classification and Regression Tree)were applied for comparison of results for the same data sample collected using questionnaire. The results were compared to find the algorithm which yields the best result in predicting the reason for student s absenteeism.