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All Journal International Journal of Artificial Intelligence and Science
Agho, Davit Cany
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Computer Science & IT

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A Hybrid Image Processing Approach for Real-Time Face Recognition in Attendance Monitoring Agho, Davit Cany; Hendrawan, Aria
International Journal of Artificial Intelligence and Science Vol. 2 No. 1 (2025): March
Publisher : Asosiasi Doktor Sistem Informasi Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63158/IJAIS.v2.i1.17

Abstract

In the era of digital transformation, institutions are increasingly adopting automation to enhance administrative efficiency, particularly in human resource management. At Tanggirejo Village Hall, a critically low employee attendance rate of 46.45% in January 2024 exposed the limitations of manual attendance systems, which are prone to errors and manipulation. This study proposes a face recognition-based attendance system utilizing OpenCV’s Haar Cascade Classifier for face detection and the Local Binary Pattern Histogram (LBPH) for face recognition. A total of 500 grayscale facial images from 10 employees were collected and processed to train and test the system. Evaluation using a Confusion Matrix revealed an accuracy of 72%, precision of 93%, and recall of 75%. While a 27% error rate was observed—primarily due to lighting inconsistencies and limited training data—the system performed reliably in real-time scenarios. The integration of these lightweight algorithms allows for fast and accurate identification, suitable for resource-constrained environments. This solution not only addresses the local attendance challenges but also presents a scalable, automated model that can be adopted by similar institutions seeking to improve productivity and operational transparency through real-time employee monitoring.
Co-Authors Aria Hendrawan, Aria