Use Data Mining for Evaluation University Student Results

Abstract

The student academic performance is based on different factors such as social and technical personality.The aim of this paper is to analyze students’ results in different years using data mining in order to extract important information, then using this information in decision making process. Thispaper used classification of supervised learning algorithm with its technologies in the area of decision tree to identify the primary influence. The implementation showed the largest influence on students’ results according to factors like batches, major, admission type and sex. It also showed that the results of batches admission in year 2007 and 2011 had the largest number of dismissed students with a percentage of 13% and 12% respectively