Prediction of the Student Graduation’s Level using C4.5 Decision Tree Algorithm
Evi Sugiana Purnamasari, Dian Palupi Rini, Sukemi Sukemi · 2019
The student graduation level is the number of student graduations, whether the graduation is categorized on time or overdue. The level of student graduation is very influential on an accreditation of the department and the accreditation of the University. The prediction of the graduation duration of students to finish his study is used by the university as reference to make policies and measures how to reduce the level of inhibition of students and graduate not on time. So, the prediction of the level of student graduation in the university needs to be determined. Students graduation level are collected from several data in the academic system and need a further processed to obtain the predicted value of future student graduation level. A method that can be used as a data processes to produce a benefit is data mining. The method used in this analysis are C4.5 Decision Tree algorithm, which is one method of classification using decision tree structure. The result of this research is a 69.79% accuracy rate value and the error rate is 30.21.