Aplikasi K-Means berbasis Web untuk Klasifikasi Kelas Unggulan
DOI:
https://doi.org/10.30812/matrik.v21i1.1473Keywords:
Data Mining, K-Means, Klasifikasi, Kelas UnggulanAbstract
MAN-1 Mataram merupakan sekolah yang berada di kota Mataram, Sekolahan ini memiliki 2 kelas yaitu kelas unggulan dan kelas biasa. Setiap tahunnya MAN-1 Mataram mengalami peningkatan penerimaan pendaftaran siswa baru diperkiran tahun kedepan siswa barunya akan mengalami peningkatan yang banyak. Banyaknya siswa yang mendaftar membuat bagian kesiswaan MAN-1 Mataram mengalami kesulitan dalam penentuan kelas, apalagi ditemuakan siswa yang dikelas unggulan didapatkan prestasi dan nilai kurang standar. Berdasarkan permasalahan tersebut tujuan dari penelitan ini adalah mewujudkan pengelompokan kelas belajar berdasarkan nilai dan prestasi siswa baru sehingga diperoleh klasifikasi kelas unggulan. Metode penelitian yang digunakan adalah algoritma K-Means yang dilengkapi dengan program aplikasi berbasis web. Hasil dari penelitian ini menunjukan bahwa algoritma k-means mampu menghasilakan pemilihan dan pembagian kelas unggulan bagi calon siswa baru sesuai dengan nilai kemampuan siswa. Penerapan kelas unggulan berdampak positif bagi peningkatan pendidikan.
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References
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[3] K. P. Sinaga and M.-S. Yang, “Unsupervised K-Means Clustering Algorithm,†in IEEE Access, 2020, vol. 8, pp. 80716–80727, doi: 10.1109/ACCESS.2020.2988796.
[4] C. Yuan and H. Yang, “Research on K-Value Selection Method of K-Means Clustering Algorithm,†Multidisciplinary Scientific Journal, vol. 2, no. 2, pp. 226–235, 2019, doi: 10.3390/j2020016.
[5] M. Z. Hossain, M. N. Akhtar, R. B. Ahmad, and M. Rahman, “A dynamic K-means clustering for data mining,†Indonesian Journal of Electrical Engineering and Computer Science, vol. 13, no. 2, pp. 521–526, 2019, doi: 10.11591/ijeecs.v13.i2.pp521-526.
[6] D. Neha and B. M. Vidyavathi, “A Survey on Applications of Data Mining using Clustering Techniques,†International Journal of Computer Applications, vol. 126, no. 2, pp. 7–12, 2015, doi: 10.5120/ijca2015905986.
[7] Ediyanto, N. Mara, and N. Satyahadewi, “Pengklasifikasian Karakteristik Dengan Metode K-Means Cluster Analysis,†Buletin Ilmiah Mat. Stat. dan Terapannya (Bimaster), vol. 02, no. 2, pp. 133–136, 2013.
[8] C. Wu et al., “k-Means Clustering Algorithm and Its Simulation Based on Distributed Computing Platform,†Journal of Wiley, vol. 2021, pp. 1–10, 2021, doi: 10.1155/2021/9446653.
[9] E. Harli, A. Fauzi, and T. H. Kusmanto, “Pengelompokkan Kelas Menggunakan Self Organizing Map Neural Network pada SMK N 1 Depok,†Jurnal Edukasi dan Penelitian Informatika (JEPIN), vol. 2, no. 2, pp. 90–95, 2016, doi: 10.26418/jp.v2i2.17574.
[10] E. B. Sambani and F. Nuraeni, “Penerapan Algoritma C4.5 Untuk Klasifikasi Pola Penjurusan di Sekolah Menengah Kejuruan (SMK) Kota Tasikmalaya,†CSRID (Computer Science Research and Its Development Journal), vol. 9, no. 3, p. 144, 2018, doi: 10.22303/csrid.9.3.2017.144-152.
[11] W. Purba, S. Tamba, and J. Saragih, “The effect of mining data k-means clustering toward students profile model drop out potential,†Journal of Physics: Conference Series, vol. 1007, no. 1, 2018, doi: 10.1088/1742-6596/1007/1/012049.
[12] A. Mahmudan, “Clustering of District or City in Central Java Based COVID-19 Case Using K-Means Clustering,†Jurnal Matematika, Statistika dan Komputasi, vol. 17, no. 1, pp. 1–13, 2020, doi: 10.20956/jmsk.v17i1.10727.
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[17] C. A. Sugianto, T. Pratiwi, and O. Riska, “K-Means Algorithm For Clustering Poverty Data in Bangka Belitung Island Province Journal of Computer Networks , Architecture and High Performance Computing,†Journal of Computer Networks , Architecture and High Performance Computing, vol. 3, no. 1, pp. 58–67, 2021.
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2021-11-26
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[1]
C. Satria and A. Anggrawan, “Aplikasi K-Means berbasis Web untuk Klasifikasi Kelas Unggulan”, MATRIK, vol. 21, no. 1, pp. 111–124, Nov. 2021, doi: 10.30812/matrik.v21i1.1473.
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