SUMMARY
The case of drop out at the Weleri STEKOM is often done by the campus. Drop out is a problem that is often done by Weleri STEKOM students because of a GPA of less than 2, Number of organizations followed, Tuition not paid for students and student who have exceeded the limit of 14 semesters. This study discusses predicting drop out students with C4.5 and ID3 decision tree methods that are useful to assist the campus in anticipating student dropouts. This study uses student data as many as 1087 students. Student data is divided into training data and testing data in order to obtain a model or rule in predicting DO students. Variable of this reseach contain V1(GPA) and then V2 (Distance beetween home and campus), V3(how long the lecture has been done), V4(Having a Job), V5(Family) and V6(school fee). This research The results of this study obtained 18 rules or rules for ID3 algorithm and 8 rules for C4.5 algorithm. The algorithm ID3 test results obtained an average of 95.17%, precision of 94.7% and recall of 96.18%, while for Decision Tree C 4.5 obtained an average of 96.45%, precision of 96.90% and recall of 95.38. This research prove that Decision using C4.5 is better for prediction of drop out students at STEKOM.