Penerapan Algoritma K-Means Clustering Untuk Mengelompokan Siswa SMK Al-Ma’rifah Berdasarkan Kehadiran
DOI:
https://doi.org/10.56995/sintek.v6i1.212Keywords:
K-Means Clustering, Kehadiran Siswa, Data Mining, Educational Data Mining, PengelompokanAbstract
Penelitian ini bertujuan untuk mengelompokkan siswa SMK Al-Ma’rifah berdasarkan pola kehadiran menggunakan algoritma K-Means Clustering. Data yang dianalisis merupakan catatan kehadiran siswa tahun ajaran 2023/2024 yang meliputi jumlah hadir, izin, sakit, alfa, dan persentase kehadiran. Tahapan pra-pemrosesan data dilakukan melalui pembersihan dan normalisasi sebelum proses clustering. Penentuan jumlah klaster optimal menggunakan Elbow Method dan Silhouette Coefficient menunjukkan bahwa tiga klaster merupakan struktur terbaik. Hasil pengelompokan menghasilkan tiga kategori siswa, yaitu sangat disiplin, cukup disiplin, dan kurang disiplin. Evaluasi kualitas klaster menggunakan Silhouette Score dan Davies–Bouldin Index menunjukkan pemisahan klaster yang baik. Penelitian ini membuktikan bahwa K-Means Clustering efektif dalam mengidentifikasi pola kehadiran siswa dan dapat mendukung pengambilan keputusan sekolah berbasis data dalam meningkatkan kedisiplinan siswa.
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