PERBANDINGAN METODE ALGORITMA C4.5 DAN NAÏVE BAYES UNTUK MEMPREDIKSI KELULUSAN MAHASISWA

Aulia Rahmayanti; Lili Rusdiana; Suratno Suratno

doi:10.21580/wjit.2022.4.1.9654

PERBANDINGAN METODE ALGORITMA C4.5 DAN NAÏVE BAYES UNTUK MEMPREDIKSI KELULUSAN MAHASISWA

- STMIK Palangkaraya, Indonesia

* - STMIK Palangkaraya, Indonesia

- STMIK Palangkaraya, Indonesia

(*) Corresponding Author

DOI: 10.21580/wjit.2022.4.1.9654

Abstract
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This study was conducted to compare the accuracy of two algorithm methods, namely the C4.5 algorithm and Naïve Bayes algorithm on a number of datasets. The sources of datasets used are student data of the Informatics Engineering Study Program (STMIK Palangkaraya) where each dataset has a different amount of data (instances) and number of attributes. Based on the results of the comparison study of the C4.5 and Naïve Bayes Algorithm for Predicting the On-time Graduation of STMIK Palangkaraya Students, the results obtained from the accuracy of the two algorithms show that the accuracy of the C4.5 Algorithm is 90% better than the Naïve Bayes algorithm, which is only 85%. The C4.5 algorithm also gives values on recall and precision of 92% and 94% better than the Naïve Bayes algorithm with values of 86% and 93%, respectively.

Keywords: C4.5 algorithm, Naïve Bayes, Graduation Prediction, STMIK Palangkaraya

Anam, C., & Santoso, H. B. (2018). Perbandingan Kinerja Algoritma C4.5 dan Naive Bayes untuk Klasifikasi Penerima Beasiswa. Jurnal Energy, 13-19.
Bahri, S., Midyanti, D. M., & Hidayati, R. (2018). Perbandingan Algoritma Naive Bayes dan C4.5 Untuk Klasifikasi Penyakit Anak. Seminar Nasional Aplikasi Teknologi Informasi (SNATi) (hal. 24-31). Yogyakarta: Jurusan Teknik Informatika, Fakultas Teknologi Industri, Universitas Islam Indonesia.
Fitriani, E. (2020). Perbandingan Algoritma C4.5 dan Naïve Bayes Untuk Menentukan Kelayakan Penerima Bantuan Program Keluarga Harapan. Jurnal Sistemasi, 103-115.
Han, J., Kamber, M., & Pei, J. (2012). Data Mining: Concepts and Techniques. Third Edition. Morgan Kaufmann Publishers.
Rusdiana, L. (2017). Perbandingan Metode K-Nearest Neighbor dan Fuzzy C-Means dalam Menentukan Predikat Kelulusan Mahasiswa. PROSIDING SNSebatik (hal. 21-26). Samarinda: STMIK Widya Cipta Dharma Samarinda.
Rusdiana, L., & Rosmiati. (2016). Aplikasi Berbasis Fuzzy C-Means Dalam Penentuan Predikat Kelulusan Mahasiswa. Jurnal Ilmu Komputer, 1-9.
Rusdiana, Lili. (2018). K-Means Algorithm to Group Students’ Academic Status at STMIK Palangka Raya. CSRID (Computer Science Research and Its Development Journal), 124-134.
Rusdiana, Lili; Sam'ani. (2017). Pemodelan K-Means Pada Penentuan Predikat Kelulusan Mahasiswa STMIK Palangka Raya. Jurnal Saintekom, 1-15.
Wati, R. (2016). Penerapan Algoritma Genetika Untuk Seleksi Fitur Pada Analisis Sentimen Review Jasa Maskapai Penerbangan Menggunakan Naive Bayes. Jurnal Evolusi, 4(1), 25-31.
Yahya, N., & Jananto, A. (2019). Komparasi Kinerja Algoritma C.45 Dan Naïve Bayes Untuk Prediksi Kegiatan Penerimaan Mahasiswa Baru. Seminar Nasional Multi Disiplin Ilmu (hal. 221-228). Semarang: Proceeding SENDI_U.