Analysis of Student Performance to License Exam Using Data Mining Techniques

Abstract:

The authors propose, in this paper, a study that aimes to highlight the contributing factors to students success in licensing exam. The study was conducted at the Faculty of Economics of Petroleum-Gas University of Ploiesti, specializing in Economic Informatics and targeted a total of 163 students who sustained the license exam in 2008-2010. The used methods are ID3 algorithm for classification by decision tree and "InfoGainAttributeEval" algorithm with Ranker search method for attributes classification.