Educational Data Analytics using Association Rule Mining and Classification

The education crisis is now widely spread in global in term of decreasing number of student and decreasing degree requirements for some jobs. Educational data mining (EDM) is recently interested in data mining area to discover useful knowledge in educational data to help educators improve their administration planning and student services. This paper proposes applying of two data mining technics in educational data. First, association rule was applied in admission data to find some knowledge for supporting admission planning. Second, decision tree was applied in course grades and job data of graduated student to predict job after graduated. The results of these studies give good knowledge for admission planning and job prediction.