The Implementation of Data Mining Techniques for Predicting Student Study Period Using the C4.5 Algorithm

Penerapan Teknik Data Mining Terhadap Prediksi Masa Studi Mahasiswa Menggunakan Algoritma C4.5

Abstract

Higher education is a key element in human resource development, and in the information age, data generated by universities is becoming increasingly abundant, including data related to students' study duration. The duration of a student's study is a crucial indicator in evaluating the efficiency and effectiveness of higher education systems. This research presents the application of the C4.5 algorithm in the analysis of student study duration data using the RapidMiner software. The research findings indicate that the IPS1 attribute (Grade Point Average for Semester 1) is a determining factor in whether a student will graduate on time or be delayed. In the data analysis, if the IPS1 value exceeds 2.950, the student is considered "Graduated," while if it is less than or equal to 2.950, they are considered "Delayed." These results provide valuable insights for decision-makers in the field of higher education, demonstrating the potential of leveraging information technology and data mining to enhance the efficiency of the education system.