Abstract:
Accumulated 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.
