Penerapan Algoritma K-Means Clustering Untuk Pengelompokan Data Absensi Siswa Menggunakan Teknologi QR Code Berbasis Web: Studi Kasus SMAN 2 Jombang - Danang Rifki Amruli; Tanhella Zein Vitadiar (METHOMIKA: Jurnal Manajemen Informatika & Komputerisasi Akuntansi, 2026)
This study develops a web-based student attendance system using QR Code technology integrated with the K-Means Clustering algorithm. The system aims to improve accuracy and efficiency in managing attendance while classifying student discipline levels based on indicators of present, late, sick, excused, and unexcused. System development applies the Waterfall model. The K-Means algorithm groups students into three clusters: high, medium, and low attendance. Precision testing shows 95.56% accuracy compared to manual teacher assessment. The system supports school digitalization by providing automated attendance recording and data-driven discipline evaluation.