Data Mining untuk Mengukur Tingkat Keaktifan Siswa dalam Mengikuti Proses Belajar pada SMP IT Andalas Cendekia
|
Keywords:
Data mining, Clustering, Metode K-Means, Belajar Mengajar, Keaktifan Siswa
AbstractThe learning process is essentially to develop the activities and creativity of students through various interactions and learning experiences. The teacher is the most important factor in the process of improving the quality of education. In addition, student learning activeness is also an important basic element for the success of the learning process. The quality and activeness of students in learning at school has a lot of diversity which makes students have different levels of understanding, this needs to be a concern for the school, especially teachers as teachers and educators of students in schools. The purpose of this study is to measure the extent to which students' ability to undergo the learning process as well as a reference and evaluation material for the school in the success of educators when carrying out the teaching and learning process. In this study the data were sourced from the Integrated Islamic Junior High School Andalas Cendekia Dharmasraya which consisted of several variables, namely the presence of student data, Academic value (knowledge), Psychomotor value (skills), Affective value (spiritual and social). In grouping the data, the appropriate method in this study is the Clustering method with the K-Means Algorithm. The results of this study obtained 3 groupings of students, namely students who are very active, students who are active and students who are less active. This research is used as a guideline for teachers in the field of study in selecting students to participate in competitions and Olympics, and can be used as a benchmark for schools of the ability of educators in the teaching and learning process. References
[1] Aranski, A., W., & Handoko, K. (2019). (2019). Data Mining Dalam Pengelompokan Nilai IQ Siswa. Jurnal Teknologi dan Open Source, 2(2), 13-22. https://ejournal.uniks.ac.id/index.php/JTOS/article/view/347
[2] Wibowo, N. (2016). Upaya Peningkatan Keaktifan Siswa Melalui Pembelajaran Berdasarkan Gaya Belajar di SMK Negeri 1 Saptosari. Jurnal Electronics, Informatics, and Vocational Education (ELINVO), 2(1), 128-139. http://journal.uny.ac.id/index.php/elinvo/article/viewFile/10621/8996 [3] Vhallah, I., Sumijan, & Santony, J. (2018). Pengelompokan Mahasiswa Potensial Drop Out Menggunaka Metode Clustering K-Means. Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi), 2(2), 572-577. https://jurnal.iaii.or.id/index.php/RESTI/article/view/308 [4] Asroni, Fitri, H., & Prasetyo, E. (2018). Penerapan Metode Clustering dengan Algoritma K-Means pada Pengelompokkan Data Calon Mahasiswa Baru di Universitas Muhammadiyah Yogyakarta (Studi Kasus: Fakultas Kedokteran dan Ilmu Kesehatan, dan Fakultas Ilmu Sosial dan Ilmu Politik). Semesta Teknika, 21(1), 60-64. https://doi.org/10.18196/st.211211 [5] Gustientiedina, Adiyaa, M., & Desnelita, Y. (2018). Penerapan Algoritma K-Means Untuk Clustering Data Obat-Obatan. Jurnal Nasional Teknologi dan Sistem Informasi, 5(1), 17 – 24. https://doi.org/10.25077/ [6] Dewi, S., Defit, S., & Yunus, Y. (2021). Akurasi Pemetaan Kelompok Belajar Siswa Menuju Prestasi Menggunakan Metode K-Means (Studi Kasus SMP Pembangunan Laboratorium UNP). Jurnal Sistim Informasi Dan Teknologi, 3(1), 28-33. https://doi.org/10.37034/jsisfotek.v3i1.98 [7] Nainggolan, R., & Purba, E. (2020). Cluster Analisys of Online Shop Product Reviews Using K-Means Clustering. International Journal of Entrepreneurship and Business Development,3(2), 142-15. https://doi.org/10.29138/ijebd.v3i02.977 [8] Binus Nusantara School of Computer science (2017). Clustering [Online] Available at : https://socs.binus.ac.id/2017/03/09/clustering/ [Accesed 27 Februari 2021] [9] Bastian, D.M Sujadi, H., & Febrianto, G. (2018S). Penerapan Algoritma K-Means Clustering Analysis Pada Penyakit Menular Manusia. Jurnal Sistem Informasi 1(14), 26-32. https://jsi.cs.ui.ac.id/index.php/jsi/article/view/566 [10] Oktarian, S., Defit, S., & Sumijan. (2020). Klasterisasi Penentuan Minat Siswa dalam Pemilihan Sekolah Menggunakan Metode Algoritma K-Means Clustering. Jurnal Informasi Dan Teknologi, 2(3), 68-75. https://doi.org/10.37034/jidt.v2i3.65 [11] Triyansyah, D., & Fitrianah, D. (2018). Analisis Data Mining Menggunakan Algoritma K-Means Clustering Untuk Menentukan Strategi Marketing. Jurnal Telekomunikasi dan Komputer, 2(8), 163-182. https://publikasi.mercubuana.ac.id/index.php/Incomtech/article/view/4174 [12] Parlambang, B., & Fauziah. (2020). Implementasi Algoritma K-Means Dalam Proses Penilaian Kuesioner Kepada Dosen Guna Mendukung Kepuasan Mahasiswa Terhadap Dosen. Jurnal Ilmiah Teknologi Dan Rekayasa , 25(2), 161-173. http://dx.doi.org/10.35760/tr.2020.v25i2.2719 [13] Informatikalogi (2016). Algoritma K-Means Clustering [Online] Available at: https://informatikalogi.com/algoritma-k-means-clustering/ [Accesed 27 Februari 2021] [14] Yudiarta, N., G., Sudarma, M., & Ariastina, W., G. (2018). Penerapan Metode Clustering Text Mining Untuk Pengelompokan Berita Pada Unstructured Textual Data. Majalah Ilmiah Teknologi Elektro, 17(3), 339-344. https://doi.org/10.24843/MITE.2018.v17i03.P06 [15] Armianti, R., I., Gaffar, A., F., O., & Putra, A., B., W. (2020). Penerapan K-Means Clustering Untuk Seleksi Frame Dominan Berbasis Ntsc Pada Obyek Bergerak. Jurnal Teknologi Informasi dan Ilmu Komputer, 7(4), 745-754. http://dx.doi.org/10.25126/jtiik.2020742184 [16] Oktarina, C., Notodiputro, K., & Indahwati, I. (2020). Comparison Of K-Means Clustering Method And K-Medoids On Twitter Data. Indonesian Journal of Statistics and Its Applications, 4(1), 189-202. https://doi.org/10.29244/ijsa.v4i1.599 [17] Mahmudan, A. (2020). Clustering of District or City in Central Java Based COVID-19 Case Using K-Means Clustering. Jurnal Matematika,Statistika & Komputasi, 17(1), 1-13. https://doi.org/10.20956/jmsk.v17i1.10727 [18] Irawan, Y. (2019). Implementation Of Data Mining For Determining Majors Using K-Means Algorithm In Students Of Sma Negeri 1 Pangkalan Kerinci. Journal of Applied Engineering and Technological Science, 1(1), 17-29. https://doi.org/10.37385/jaets.v1i1.18 [19] Nurdiawan, O., & Pratama, F.A. (2019). Implementasi Algoritma K-Means Dalam Penentuan Prioritas Rehabilitasi Daerah Aliran Sungai Cipunagara. Jurnal Nasional Informatika & Teknologi Jaringan 1(4), 76-81. https://doi.org/10.30743/infotekjar.v4i1.1633 [20] Adhitama, R., Burhanuddin, A., & Ananda, R. (2020). Penentuan Jumlah Cluster Ideal Smk Di Jawa Tengah Dengan Metode X-Means Clustering Dan K-Means Clustering. JIKO (Jurnal Informatika dan Komputer), 3(1), 1-5. http://dx.doi.org/10.33387/jiko.v3i1.1635 |
Published
2021-09-30
Issue
Section
Articles
How to Cite
Triandini, M., Defit, S., & Nurcahyo, G. W. (2021). Data Mining untuk Mengukur Tingkat Keaktifan Siswa dalam Mengikuti Proses Belajar pada SMP IT Andalas Cendekia. Jurnal Informasi Dan Teknologi, 3(3), 167-173. https://doi.org/10.37034/jidt.v3i3.120
|
