Aplikasi Data Mining Untuk Memprediksi Kelulusan Mahasiswa Menggunakan Algoritme C4.5 - Febrian Pandu Widhianto; Ahmad Afif Supianto; Nanang Yudi Setiawan (Jurnal Pengembangan Teknologi Informasi dan Ilmu Komputer, 2019)
Brawijaya University Faculty of Computer Science had many students. The Information system study program from the generation 2011 to 2018 has 1817 college students, but the number of students who graduate and enter is disproportionate, so that students who do not graduate on time can reduce accreditation from major, faculty or university. Based on that, the amount of data available can be used as an algorithm in data mining to predict students graduates. The C4.5 algorithms are one of the algorithms that can be used in predicting students graduation by producing a rule in the form of a decision tree. The data used in this study is student academic data from semester 1 - 4. Using the algorithm C4.5 generated accuracy by 90.9%, while ROC's curve of AUC values is 0.8232. the usability value produced from SUS is 67.5. The output generated by a dashboard display with some graphic that contains the graduation percentage, the graduation recapitulation of each generation and the value details of students, is also a form for data input that can be used by the head of program information system study program to predict by uploading collective data or linear data.