Informatics Publishing Limited

Gurmeet Kaur ¹, Williamjit Singh ²

Affiliations
1 Punjabi University, Patiala, IN
2 Department of CE, Punjabi University, Patiala, IN

Abstract

Data mining is widely used in educational field to find the problems arise in this field. Student performance is of great concern in the educational institutes where several factors may affect the performance. For prediction the three required components are: Parameters which affect the student performance, Data mining methods and third one is data mining tool. These Parameters may be psychological, personal, environmental. We conduct this study to maintain the education quality of institute by minimizing the diverse affect of these factors on student's performance. In this Paper, Prediction of student Performance is done by applying Naïve bayes and J48 decision tree classification techniques WEKA tool. By applying data mining techniques on student data we can obtain knowledge which describes the student performance. This knowledge will help to improve the education quality, student's performance and to decrease failure rate. All these will help to improve the quality of institute.

Keywords

Prediction, Naive Bayes, J48, Weka Tool.

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