The Study of Decision Tree Algorithm For Classification of Student Graduation (Case Study : Faculty of Economics, University of Garut)

The academic performance is one of aspect which has remained the benchmark of the success in learning activities at the university. The indicator of academic performance in the university is the students able to complete their studies on time. Unfortunately, the problem regarding academic performance was associated with the completion time of student studies in Faculty of Economics,University of Garut. In this research explore the model that able to classify the graduation of student through the data mining classification technique by Decision Tree Algorithm. The classification conducted by evaluating the academic performance based on Semester Performance Index (IPS) and Semester Credit Unit (SKS) during two years in the beginning and use the demographics of students as attributes that will be used in the dataset. Based on the examinations that conducted by using k-fold cross validation, there are 8 attributes that influence the graduation of students. The model that represented able to applied for classify the active students in 2016 and 2017 that indicate accuracy value of 79.53% and recall value was 19.23%