K-Means Algorithm for Clustering High-Achieving Student at Madrasah Tsanawiyah Yami Waled
DOI:
https://doi.org/10.59934/jaiea.v4i3.771Keywords:
K-Means, Clustering, Education, Academic Achievement, Data MiningAbstract
This study aims to apply the K-Means algorithm to cluster students based on their mathematics grades at Madrasah Tsanawiyah Islamiyyah Yami Waled. By categorizing students into clusters of low, medium, and high academic achievement, the institution can develop more effective and targeted learning strategies. The data consisted of semester mathematics grades from 112 students, analyzed using the K-Means clustering algorithm. Clusters were evaluated using the Davies-Bouldin Index (DBI), with results showing three distinct clusters: Cluster 0 (low achievers, 54 students), Cluster 1 (medium achievers, 37 students), and Cluster 2 (high achievers, 21 students). The DBI score of 0.893 indicates good clustering quality, providing valuable insights for personalized learning approaches.
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F. P. Dewi, P. S. Aryni, and Y. Umaidah, “Implementasi Algoritma K-Means Clustering Seleksi Siswa Berprestasi Berdasarkan Keaktifan dalam Proses Pembelajaran,” JISKA (Jurnal Inform. Sunan Kalijaga), vol. 7, no. 2, pp. 111–121, 2022, doi: 10.14421/jiska.2022.7.2.111-121.
E. A. Saputra and Y. Nataliani, “Analisis Pengelompokan Data Nilai Siswa untuk Menentukan Siswa Berprestasi Menggunakan Metode Clustering K-Means,” J. Inf. Syst. Informatics, vol. 3, no. 3, pp. 424–439, 2021, doi: 10.51519/journalisi.v3i3.164.
Haris Kurniawan, Sarjon Defit, and Sumijan, “Data Mining Menggunakan Metode K-Means Clustering Untuk Menentukan Besaran Uang Kuliah Tunggal,” J. Appl. Comput. Sci. Technol., vol. 1, no. 2, pp. 80–89, 2020, doi: 10.52158/jacost.v1i2.102.
A. Nugraha, O. Nurdiawan, and G. Dwilestari, “PENERAPAN DATA MINING METODE K-MEANS CLUSTERING UNTUK ANALISA PENJUALAN PADA TOKO YANA SPORT,” 2022.
J. Hutagalung, “Pemetaan Siswa Kelas Unggulan Menggunakan Algoritma K-Means Clustering,” JATISI (Jurnal Tek. Inform. dan Sist. Informasi), vol. 9, no. 1, pp. 606–620, 2022, doi: 10.35957/jatisi.v9i1.1516.
A. Bahauddin, A. Fatmawati, and F. Permata Sari, “Analisis Clustering Provinsi Di Indonesia Berdasarkan Tingkat Kemiskinan Menggunakan Algoritma K-Means,” J. Manaj. Inform. dan Sist. Inf., vol. 4, no. 1, pp. 1–8, 2021, doi: 10.36595/misi.v4i1.216.
Y. Filki, “Algoritma K-Means Clustering dalam Memprediksi Penerima Bantuan Langsung Tunai (BLT) Dana Desa,” J. Inform. Ekon. Bisnis, vol. 4, pp. 166–171, 2022, doi: 10.37034/infeb.v4i4.166.
S. Dewi, S. Defit, and Y. Yuhandri, “Akurasi Pemetaan Kelompok Belajar Siswa Menuju Prestasi Menggunakan Metode K-Means,” J. Sistim Inf. dan Teknol., vol. 3, pp. 28–33, 2021, doi: 10.37034/jsisfotek.v3i1.40.
N. Mirantika, “Penerapan Algoritma K-Means Clustering Untuk Pengelompokan Penyebaran Covid-19 di Provinsi Jawa Barat,” Nuansa Inform., vol. 15, no. 2, pp. 92–98, 2021, doi: 10.25134/nuansa.v15i2.4321.
T. Asy Aria, M. Julkarnain, and F. Hamdani, “KLIK: Kajian Ilmiah Informatika dan Komputer Penerapan Algoritma K-Means Clustering Untuk Data Obat,” Media Online, vol. 4, no. 1, pp. 649–657, 2023, doi: 10.30865/klik.v4i1.1117.
M. Djaka Permana, A. Lia Hananto, E. Novalia, B. Huda, and T. Paryono, “Klasterisasi Data Jamaah Umrah pada Tanurmutmainah Tour Menggunakan Algoritma K-Means,” J. KomtekInfo, vol. 10, pp. 15–20, 2023, doi: 10.35134/komtekinfo.v10i1.332.
V. Ramadhan and Apriade Voutama, “Clustering Menggunakan Algoritma K-Means Pada Penyakit ISPA di Puskesmas Kabupaten Karawang,” J. Pendidik. dan Konseling, vol. 4, no. 5, pp. 462–473, 2022.
C. A. Sugianto, A. H. Rahayu, and A. Gusman, “Algoritma K-Means untuk Pengelompokkan Penyakit Pasien pada Puskesmas Cigugur Tengah,” J. Inf. Technol., vol. 2, no. 2, pp. 39–44, 2020, doi: 10.47292/joint.v2i2.30.
A. Sulistiyawati and E. Supriyanto, “Implementasi Algoritma K-means Clustring dalam Penetuan Siswa Kelas Unggulan,” vol. 15, no. 2.
H. Syahputra, “Clustering Tingkat Penjualan Menu (Food and Beverage) Menggunakan Algoritma K-Means,” J. KomtekInfo, vol. 9, pp. 29–33, 2022, doi: 10.35134/komtekinfo.v9i1.274.
I. Virgo, S. Defit, and Y. Yuhandri, “Klasterisasi Tingkat Kehadiran Dosen Menggunakan Algoritma K-Means Clustering,” J. Sistim Inf. dan Teknol., vol. 2, pp. 23–28, 2020, doi: 10.37034/jsisfotek.v2i1.17.
D. Zakiyah, N. Merlina, and N. A. Mayangky, “Penerapan Algoritma K-Means Clustering Untuk Mengetahui Kemampuan Karyawan IT,” Comput. Sci., vol. 2, no. 1, pp. 59–67, 2022, doi: 10.31294/coscience.v2i1.623.
K. Gustipartsani, N. Rahaningsih, R. Danar Dana, and I. Yulia Mustafa, “Data Mining Clustering Menggunakan Algoritma K-Means Pada Data Kunjungan Wisatawan Di Kabupaten Karawang,” JATI (Jurnal Mhs. Tek. Inform., vol. 7, no. 6, pp. 3595–3601, 2024, doi: 10.36040/jati.v7i6.8282.
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