A SURVEY ON STUDENT‘S ABSENTEEISM AT UNDER GRADUATE LEVEL USING NAÏVE BAYES ALGORITHM FOR CATEGORICAL DATASET

Authors

Dr. N. Venkatesan (Associate Professor)
Bharathiyar College of Eng&Tech, Karaikal. 

S. Muthukumaran (Assistant Professor) & K. Arunmozhi Arasan (HOD & Assistant Professor)
Siga College of Management and Computer Science, Villupuram.

Abstract

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 can be applied on the educational data for predicting the students behavior. This paper focus on the reason for the leave taken by the student in an academic year. The first step of the study is to gather student’s data by using a questionnaire. We collect data from 123 students who were under graduate from a private college which is situated in a semi-rural area. The second step is to clean the data which is appropriate for mining purpose and choose the relevant attributes the classification is done using the gender attribute. This paper presents the use of Naïve Bayes Algorithm in predicting the reason for student’s absenteeism. The efficiency of Naïve Bayes algorithm on classifying a given dataset was measured using the confusion matrix obtained in tanagra. This knowledge is used to identify the reason for the leave taken by the student and help to improve the quality of the environment and also to improve the performance of the student.