Penerapan Algoritma K-Means Clustering Untuk Pengelompokan Data Absensi Siswa Menggunakan Teknologi QR Code Berbasis Web

Studi Kasus SMAN 2 Jombang

Authors

  • Danang Rifki Amruli Universitas Hasyim Asy'ari
  • Tanhella Zein Vitadiar Universitas Hasyim Asy'ari

DOI:

https://doi.org/10.46880/jmika.Vol10No1.pp53-61

Keywords:

Attendance, QR Code, K-Means Clustering, Student discipline, Web system

Abstract

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.

References

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Published

2026-04-27

Issue

Vol. 10 No. 1 (2026): METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi

Section

METHOMIKA: Jurnal Manajemen Informatika & Komputersisasi Akuntansi

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Copyright (c) 2026 Danang Rifki Amruli, Tanhella Zein Vitadiar

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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.