Penerapan Algoritma Decision Tree untuk Klasifikasi Kelulusan Mahasiswa Berdasarkan Faktor Akademik dan Sosial - Dofiyanto; Fatah, Zaehol (JISCO : Journal of Information System and Computing, 2025)
This research aims to employ the C4.5 Decision Tree technique to classify the results of student graduation. This is achieved by taking into account both their scholastic performance and social factors. Scholastic performance indicators encompass the student's overall grade average, their academic status, and how often they attend classes, whereas social factors include their age, whether they are married, and their engagement in extracurricular activities. The information utilized was taken from an internal compilation of student information, which was refined and modified with the RapidMiner program. To ensure the correctness of the predictions, the categorization model was confirmed through the implementation of a 10-fold cross-validation strategy. The results of the tests demonstrated an 89.44% level of correctness, as well as a 91.38% level of precision and a 90.28% rate of recall, showing that the model functions at a level that is both remarkably successful and reliable. These discoveries reinforce the idea that the C4.5 Decision Tree algorithm is capable of accurately determining the patterns in student graduation through the integration of both scholastic and social elements. This can then act as a foundation for making scholastic decisions to improve the efficiency of the process of higher education.