Sistem Klasifikasi Mahasiswa Cum Laude Menggunakan Algoritma Decision Tree C5.0

Grade Point Average (GPA) is an indicator of academic quality in the accreditation process of study programs, and the percentage of students achieving cum laude distinction reflects the quality of higher education. However, at Politeknik Negeri Bengkalis, the number of students who do not achieve cum laude distinction is still higher, indicating the need for analysis to identify the factors influencing this achievement. This study aims to develop a cum laude student classification system using the Decision Tree C5.0 algorithm with the Rapid Application Development (RAD) method. The dataset consists of 154 student records with a two-level classification model, where the first level is based on academic guidelines and the second level is based on questionnaire data. The results show an accuracy of 100% for the first-level classification and 90% for the second-level classification based on confusion matrix evaluation. Therefore, the system is expected to assist the study program in identifying students who have the potential to achieve cum laude distinction more quickly and accurately.