Algoritma C4.5 Dalam Data Mining Untuk Menentukan Klasifikasi Penerimaan Calon Mahasiswa Baru - Haryoto, Parawystia Prabasini; Okprana, Harly; Saragih, Ilham Syahputra (TIN: Terapan Informatika Nusantara, 2021)
Conducting a graduation classification of prospective freshmen at a college should be best not only by the written exam value criteria but also the interview test, and other things that can serve as assessment parameters. In this study an increased parameters for classifying potential students in the scarlet hyperlinate's post-collegiate bud with deep learning methods using a c4 algorithc.5. With this method of classification, it is hoped to help academicians determine the criteria of active and exemplary freshman candidates. From experiment with the rapidminer's software on the data of students who have registered from 2016 to 2020, obtained an active student classification defined by the value of the interview being the first node, coupled with the value of an academic potential test. In the meantime, it is found that what can affect a student's performance is the school's origin and duration of college. Students who continue studying => 4 years tend to have grades and achievements under those who continue to study at three to four years. Based on research, score of accuracy at 81.32%.