Simbolon, Alexander2023-04-102023-04-102023-01PerpustakaanElfitrahttps://repository.unri.ac.id/handle/123456789/10915Accumulated student’s data in University cause of admission of new student in every years can be managed to create usefull information. One of them is by using data mining. The purpose of this study is to implement the C4.5 algorithm model to predict student graduation. Student’s data such as ID number, Entry Path, Regional Origin, Gender, GPA, GPA from the first semester to the fifth semester and student graduation (is it on time or not) will be analyzed using the C4.5 algorithm method. . The results of data management are in the form of decision trees and rules that will be used as criteria for predicting student graduation. Using 201 training data and 148 target data that managed in prediction system, shows that the system goes well with the accuracy rate up to 80,58%. The accuracy level of the system's prediction will increase along with the increase in the amount of training data in the system. The more data used, the accuracy level will increace.endata miningstudent graduationC4.5riau universityArticle