PENGELOMPOKAN MAHASISWA BERDASARKAN MOTIVASI BELAJAR MENGGUNAKAN K-MEANS (STUDI KASUS: PRODI SISTEM INFORMASI STMIK DHARMA WACANA)
(1) Prodi Sistem Informasi, STMIK Dharma Wacana Metro, Lampung
(2) Prodi Sistem Informasi, STMIK Dharma Wacana Metro, Lampung
Corresponding Author
Abstract
Student motivation to learn can be seen from the student's initiative in using their time to study. There are several factors that influence students to be motivated in learning. In this study, researchers used variables in the form of intrinsic motivation, extrinsic motivation, learning goals, learning satisfaction, learning attitudes and perceived value to find out students who had high, medium or low motivation. This research uses K-Means to group students based on learning motivation to find out how much motivation students have in learning.
Keywords
References
S. M. Efastri, A. A. Putri, and S. Fadillah, “Hubungan Ketergantungan Gadget dengan Pendekatan REBT terhadap Motivasi Belajar Mahasiswa Program Studi PG-PAUD FKIP UNILAK,” PAUD Lect. J. Pendidik. Anak Usia Dini, vol. 1, no. 2, pp. 134–143, 2018.
V. L. Siswati, “Studi Empiris tentang Pengaruh Budaya Organisasi, Gaya kepemimpinan, Motivasi Belajar dan Manajemen Pembelajaran terhadap Kinerja Akademik Mahasiswa pada Sekolah Tinggi Ilmu Tarbiyah Raden Wijaya Mojokerto,” Progressa J. Islam. Relig. Instr., vol. 2, no. 1, p. 31, 2019.
B. Widharyanto, “Menimbang Preferensi Modalitas Belajar Pemelajar Nusa Tenggara Timur : Kajian Gaya Belajar Dan Strategi Belajar Bahasa,” vol. 1, no. 1, pp. 10–19, 2021.
A. Rahmawati and S. Hudayah, “Pengaruh kepemimpinan dan budaya organisasi serta karakteristik pekerjaan terhadap kepuasan kerja dan motivasi Effect of leadership and organizational culture and job characteristics on job satisfaction and motivation,” Juranal Manajeman, vol. 11, no. 2, pp. 103–115, 2019.
D. A. C, D. A. Baskoro, L. Ambarwati, and I. W. S. Wicaksana, Belajar Data Mining dengan RapidMiner. 2013.
S. A. Ruli Utami, Ferry Andhika Primadana, “Aplikasi Customer Relathionship Management Untuk Klasifikasi Pelanggan Menggunakan Algoritma C4.5,” J. MEDIA Inform. BUDIDARMA, vol. 6, no. 3, pp. 1426–1434, 2022.
K. Faradila Ilena Putri, Retno Damayanti, “Penerapan Algoritma K-Means Untuk Mengelompokan Kecamatan Di Kabupaten Gunungkidul Berdasarkan Program Keluarga Harapan,” in Prosiding Seminar Nasional Matematika, Statistika, dan Aplikasinya, 2022, pp. 408–418.
S. Mukodimah, M. Muslihudin, D. R. Mustofa, and D. Susianto, “Naive Bayes Classifier Method Analysis and Support Vector Machine ( SVM ) Student Graduation Prediction,” NEUROQUANTOLOGY, vol. 20, no. 12, pp. 3522–3533, 2022.
I. H. Hendra Marcos, “Implementasi Data Mining Untuk Klasifikasi Nasabah Kredit Bank"X" Menggunakan Classification Rule,” in SEMANASTEKNOMEDIA 2014, 2014, pp. 1–7.
T. W. Agung Waluyo, Moch. Abdul Mukid, “Perbandingan Analisis Klasifikasi Nasabah Kredit Menggunakan Regresi Logistik Biner Dan Cart (Classification And Regression Trees),” J. Gaussian, vol. 4, no. 2, pp. 215–225, 2015.
K. Rismayanti, Fera Damayanti, “Penerapan Data Mining Algoritma C4.55 Dalam Menentukan Rekam Jejak Kinerja Dosen STT Harapan Medan,” J. Penelit. Tek. Inform., vol. 3, no. 1, pp. 99–104, 2018.
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DOI: 10.56327/jurnaltam.v15i1.1663
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