STUDENT GRADUATION PREDICTION USING DECISION TREE METHOD WITH C4.5 ALGORITHM - Sarbaini, Sarbaini; Ulfa, Fara (Program Studi Matematika, Universitas Nusa Cendana, 2024)
One of the determinants of the quality of higher education is the percentage of student’s ability to complete their studies on time. However, in practice, few students can complete their studies in higher education on time. Graduation prediction is one of the things that can be done to increase student graduation so that early prevention or handling of students who have the opportunity to not graduate on time can be done. The aim of this research is to find out and analyze the use of the Decision Tree Method with the application of the C4.5 Algorithm to effectively predict student graduation on time. The data used is that of Mathematics students at UIN SUSKA RIAU's Faculty of Science and Technology. The decision tree was constructed using 150 training data and processed using the C4.5 algorithm to generate 40 rules, which were then tested using 150 data sets with an accuracy of 78.6667 percent and an AUC of 0.8363.