Pengembangan Sistem Pengelompokan Belajar Mahasiswa pada Matakuliah Struktur Data dengan Metode K-Means
Abstract
The development of science and technology requires tertiary institutions as formal education institutions, to be able to produce qualified and competent graduates. Learning about higher education needs to be more innovative and creative in producing learning and responsive to labor needs. "Successful constraints of lecturers in teaching Data Structure subjects do not have learning models that approach students with abstract theories that are difficult for students to understand, to overcome these conflicts. learn with the Application of Cooperative Oriented Problems. However, in terms of grouping learning with the application of this method, it still takes a relatively long time to do individual testing several times to find a suitable group, so that the learning grouping is less than optimal. The method used in this study is K-Means Clustering, from the software that was built to help instructors in the subject of data structure in the process of grouping tutoring students. Grouping methods can be implemented to build valid student guidance grouping software.
Keywords: Learning Grouping System, Clustering, K-Means
References
Asroni, A., & Adrian, R. (2015). Penerapan Metode K-Means untuk Clustering Mahasiswa Berdasarkan Nilai Akademik Dengan Weka Interface Studi Kasus pada Jurusan Teknik Informatika UMM Magelang. Jurnal Ilmiah Semesta Teknika,18 (1), 76–82
Hamzah, M. L., Rukun, K., Fahmi, R., Purwati, A. A., Hamzah., & Zarnelly, Z. (2019). A Review of Increasing Teaching and Learning Database Subjects in Computer Science, Espacios, 40(26), 6. Retrieved from http://www.revistaespacios.com/a19v40n26/19402606.html
Li, L., Luo, X., & Chen, H. (2015). Clustering Students for Group-Based Learning in Foreign Language Learning. International Journal of Cognitive Informatics and Natural Intelligence, 9(2), 55-72
Poerwanto, B., & Fa’rifah, R. Y. (2016). Analisis Cluster Menggunakan Algoritma K-Means, d’ComPutarE. Jurnal Ilmiah Teknologi Informasi
Suprawoto, T. (2016). Klasifikasi Data Mahasiswa Menggunakan Metode K- Means untuk Menunjang Pemilihan Strategi Pemasaran, Jurnal Informatika dan Komputer (JIKO), 1(1), 12–18
Syafrianto, A. (2012). Perancangan Aplikasi K-means untuk Pengelompokan Mahasiswa Stmik El-Erhama Yogyakarta Berdasarkan Frekuensi Kunjungan ke Perpustakaan dan IPK. Jurnal Teknologi Informasi dan Ilmu Komputer (FAHMA), http://jurnal.stmikelrahma.ac.id/assets/file/Andri%20Syafrianto_stmikelrahma.pdf
Wardhani, A. (2016). K-Means Algorithm Implementation for Clustering of Patients Disease In Kajen Clinic of Pekalongan. Jurnal Transformatika, 14(1), 30-37.doi:http://dx.doi.org/10.26623/transformatika.v14i1.387
Yulia, D., & Setiawan, A. (2016). Penerapan Metode Clustering K-Means dalam Penjualan Produk. Jurnal Media Infotama, 12(2), 148–57
