Decision Tree Penentuan Masa Studi Mahasiswa Prodi Teknik Informatika (Studi Kasus: Fakultas Teknik dan Komputer Universitas Harapan Medan) - Rismayanti Rismayanti (Query: Journal of Information Systems, 2018)
University databases such as technology and computer department at Harapan university of Medan keeps academic, administrative and students’ data in large volume. If the data is mined properly then it has been known the pattern or knowledge to make a decision. By having the data of Informatics Department graduated students, the information that obtained is the decision tree with the rules to predict the studying period of the informatics Department students at Harapan University of Medan. The data used for designing the decision tree consists of 6 predictor attributes (Gender, Region, Specialization, School, Parrents’  occupation and GPA) and 2 target attributes (Passed “On Time” and “Late”). Data analysis used C4.5 algorithm, it used 30 samples taken randomly from alumni data. The research results show the decision tree model with the rules of the students who pass “On Time” is students who have a high GPA and students who have a medium GPA with the focus robotics. Keywords : Data Mining,  C4.5 Algorithm, Decision Tree.