Penerapan Algoritma C4.5 Untuk Analisa Tingkat Keberhasilan Mahasiswa Dalam Pembelajaran Praktikum di Masa Pandemi
Abstract
Practical learning is a method of learning in which students conduct experiments directly by applying the theories they have learned and proving what they have learned in order to better understand what they have learned. The success rate of students towards practical learning is one of the factors that can improve the quality of higher education and can facilitate lecture activities. To analyze the success rate of students towards practicum learning, they can use the C4.5 algorithm by looking at the highest gain. The C4.5 algorithm is one of the algorithms in data mining whose results are identical to the decision tree. Several parameters used for this research are motivation factor, learning method factor, learning material factor, and facility factor. This research was conducted with the aim of helping universities determine the level of student success in practicum learning using the C4.5 algorithm as much as 200 data. The results of the study showed an accuracy of 82.00% with the facility factor being the highest factor. So that the results obtained can help the campus in improving the learning process.
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References
N. Rofiqo, A. P. Windarto, and E. Irawan, “Penerapan Algoritma C4.5 pada Penentuan Tingkat Pemahaman Mahasiswa Terhadap Matakuliah,” Pros. Semin. Nas. Ris. Inf. Sci., vol. 1, no. September, p. 307, 2019, doi: 10.30645/senaris.v1i0.36.
S. T. Siska, “ANALISA DAN PENERAPAN DATA MINING UNTUK MENENTUKAN KUBIKASI AIR TERJUAL BERDASARKAN PENGELOMPOKAN PELANGGAN MENGGUNAKAN ALGORITMA K-MEANS CLUSTERING,” J. Teknol. Inf. Pendidik., vol. 9, no. 1, pp. 86–93, 2016.
E. Buulolo, “Data Mining Untuk Perguruan Tinggi.” p. 91, 2020.
E. Prasetyowati, “DATA MINING Pengelompokan Data untuk Informasi dan Evaluasi,” Duta Media Publishing. pp. 97–98, 2017.
V. M. Paul, I. Gunawan, B. E. Damanik, I. Parlina, and W. Syahputra, “DALAM MENENTUKAN KELAYAKAN PENERIMAAN BANTUAN BEDAH RUMAH PADA DESA TIGA DOLOK Paul V . M ., Indra Gunawan , Bahrudi Efendi Damanik , Iin Parlina dan Widodo Saputra STIKOM Tunas Bangsa Pematangsiantar Abstrak Penerapan Data Mining Menggunakan Algoritma C4,” vol. 1, pp. 396–409, 2021.
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.
A. Bastian, H. Sujadi, and G. Febrianto, “Penerapan Algoritma K-Means Clustering Analysis Pada Penyakit Menular Manusia (Studi Kasus Kabupaten Majalengka),” no. 1, pp. 26–32.
C. Astria, A. P. Windarto, and D. Hartama, “Penerapan K-Medoid Pada Rumah Tangga Yang Memiliki Sumber Penerangan Listrik Pln Berdasarkan Provinsi,” KOMIK (Konferensi Nas. Teknol. Inf. dan Komputer), vol. 3, no. 1, pp. 604–609, 2019, doi: 10.30865/komik.v3i1.1667.
S. Budi, “Text Mining Untuk Analisis Sentimen Review Film Menggunakan Algoritma K-Means,” Techno.Com, vol. 16, no. 1, pp. 1–8, 2017, doi: 10.33633/tc.v16i1.1263.
D. Jollyta, W. Ramdhan, and M. Zarlis, “Konsep Data Mining Dan Penerapan.” Deepublish, 2020.
D. Nofriansyah and G. W. Nurcahyo, “Algoritma Data Mining Dan Pengujian,” Algoritma Data Mining dan Pengujian. pp. 1–3, 2019.
J. Suntoro, “DATA MINING : Algoritma dan Implementasi dengan Pemrograman php.” p. 179, 2019.
N. Iriadi, “Penerapan Algoritma Klasifikasi Data Mining Dalam,” KNiST, vol. XIV, no. 2, pp. 120–129, 2017.
E. P. Cynthia and E. Ismanto, “Metode Decision Tree Algoritma C.45 Dalam Mengklasifikasi Data Penjualan,” J. Ris. Sist. Inf. Dan Tek. Inform., vol. (3) Juli, no. July, pp. 1–13, 2018.
Y. Mardi, “Data Mining : Klasifikasi Menggunakan Algoritma C4.5,” Edik Inform., vol. 2, no. 2, pp. 213–219, 2017, doi: 10.22202/ei.2016.v2i2.1465.
A. Wanto et al., Data Mining Algoritma & Implementasi, vol. 4, no. 3. 2020.
F. F. Harryanto and S. Hansun, “Penerapan Algoritma C4.5 untuk Memprediksi Penerimaan Calon Pegawai Baru di PT WISE,” Maret, vol. 3, no. 2, p. 95, 2017.
D. Mining, “Belajar Mudah Algoritma Data Mining Clustering : k-means,” pp. 2–6.
R. Nofitri and M. A. Sembiring, “Analisa Kinerja Algoritma C4.5 Dalam Memprediksi Pencapaian Profit,” Ina. Pap., vol. 1, pp. 73–79, 2017.
Y. S. Luvia, A. P. Windarto, S. Solikhun, and D. Hartama, “Penerapan Algoritma C4.5 Untuk Klasifikasi Predikat Keberhasilan Mahasiswa Di Amik Tunas Bangsa,” Jurasik (Jurnal Ris. Sist. Inf. dan Tek. Inform., vol. 1, no. 1, p. 75, 2017, doi: 10.30645/jurasik.v1i1.12.
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