Algoritma C4.5 Dalam Data Mining Untuk Menentukan Klasifikasi Penerimaan Calon Mahasiswa Baru
-
Parawystia Prabasini Haryoto
*
STIKOM Tunas Bangsa, Pematangsiantar,
Indonesia
- Harly Okprana STIKOM Tunas Bangsa, Pematangsiantar, Indonesia
- Ilham Syahputra Saragih STIKOM Tunas Bangsa, Pematangsiantar, Indonesia (*) Corresponding Author
Abstract
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%.
Downloads
References
S. Haryati, A. Sudarsono, and E. Suryana, “Implementasi Data Mining Untuk Memprediksi Masa Studi Mahasiswa Menggunakan Algoritma C4.5 (Studi Kasus: Universitas Dehasen Bengkulu),” J. Media Infotama, vol. 11, no. 2, pp. 130–138, 2015.
Taufiq and Y. Yudihartanti, “Penerapan Algoritma C4.5 Klasifikasi Tingkat Kelulusan Mahasiswa,” Semin. Nas. Ilmu Komput., vol. 2, pp. 153–162, 2019.
A. Rohman and A. Rufiyanto, “Implementasi Data Mining Dengan Algoritma Decision Tree C4 . 5 Untuk Prediksi Kelulusan Mahasiswa Di Universitas,” Proceeding SINTAK 2019, pp. 134–139, 2019.
A. H. Nasrullah, “Penerapan Metode C4.5 untuk Klasifikasi Mahasiswa Berpotensi Drop Out,” Ilk. J. Ilm., vol. 10, no. 2, pp. 244–250, 2018, doi: 10.33096/ilkom.v10i2.300.244-250.
S. Takalapeta, “Penerapan Data Mining Untuk Menganalisis Kepuasan Konsumen Menggunakan Metode Algoritma C4.5,” J I M P - J. Inform. Merdeka Pasuruan, vol. 3, no. 3, pp. 34–38, 2018, doi: 10.37438/jimp.v3i3.186.
E. Elisa, “Analisa dan Penerapan Algoritma C4.5 Dalam Data Mining Untuk Mengidentifikasi Faktor-Faktor Penyebab Kecelakaan Kerja Kontruksi PT.Arupadhatu Adisesanti,” JOIN, vol. 2, no. 1, pp. 36–41, 2017.
L. N. Rani, “Klasifikasi Nasabah Menggunakan Algoritma C4.5 Sebagai Dasar Pemberian Kredit,” INOVTEK Polbeng - Seri Inform., vol. 1, no. 2, p. 126, 2016, doi: 10.35314/isi.v1i2.131.
S. Sularno and P. Anggraini, “Penerapan Algoritma C4.5 Untuk Klasifikasi Tingkat Keganasan Hama Pada Tanaman Padi (Studi Kasus : Dinas Pertanian Kabupaten Kerinci),” J. Sains dan Inform., vol. 3, no. 2, p. 161, 2017, doi: 10.22216/jsi.v3i2.2779.
D. Ardiansyah, “Algoritma C4.5 Untuk Klasifikasi Calon Peserta Lomba Cerdas Cermat Siswa Smp Dengan Menggunakan Aplikasi Rapid Miner,” J. Inkofar, vol. 1, no. 2, pp. 5–12, 2019, doi: 10.46846/jurnalinkofar.v1i2.29.
R. P. S. Putri and I. Waspada, “Penerapan Algoritma C4.5 pada Aplikasi Prediksi Kelulusan Mahasiswa Prodi Informatika,” Khazanah Inform. J. Ilmu Komput. dan Inform., vol. 4, no. 1, p. 1, 2018, doi: 10.23917/khif.v4i1.5975.
Bila bermanfaat silahkan share artikel ini
Berikan Komentar Anda terhadap artikel Algoritma C4.5 Dalam Data Mining Untuk Menentukan Klasifikasi Penerimaan Calon Mahasiswa Baru
Pages: 358-364
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under Creative Commons Attribution 4.0 International License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (Refer to The Effect of Open Access).
