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All Journal JTEV (Jurnal Teknik Elektro dan Vokasional Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic Prosiding SNATIF SMATIKA Proceeding of the Electrical Engineering Computer Science and Informatics IJFAC (Indonesian Journal of Fundamental and Applied Chemistry) JETT (Jurnal Elektro dan Telekomunikasi Terapan) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL MEDIA INFORMATIKA BUDIDARMA VOLT : Jurnal Ilmiah Pendidikan Teknik Elektro CYCLOTRON Jurnal Teknologi Sistem Informasi dan Aplikasi JURIKOM (Jurnal Riset Komputer) EDUMATIC: Jurnal Pendidikan Informatika Jurnal Qua Teknika bit-Tech Jurnal Sistem Komputer dan Informatika (JSON) Jurasik (Jurnal Riset Sistem Informasi dan Teknik Informatika) Multidiciplinary Output Research for Actual and International Issue (Morfai Journal) International Journal of Research in Vocational Studies (IJRVOCAS) BEES: Bulletin of Electrical and Electronics Engineering Sisfo: Jurnal Ilmiah Sistem Informasi Jurnal Polimesin semanTIK Smatika Jurnal : STIKI Informatika Jurnal
Ahmad Taqwa
Politeknik Negeri Sriwijaya
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Real-Time Student Attendance Recognition Using a Centroid Based MTCNN–ArcFace Framework Suci Putri Widyani; Suroso Suroso; Ahmad Taqwa
Jurnal Pendidikan Informatika (EDUMATIC) Vol 10 No 2 (2026): Edumatic: Jurnal Pendidikan Informatika (IN PRESS)
Publisher : Universitas Hamzanwadi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29408/edumatic.v10i2.35448

Abstract

Student attendance remains susceptible to proxy attendance and operational inefficiencies, while many face recognition systems are evaluated only on benchmark datasets and rarely investigate identity representation strategies under real-world educational conditions. This study evaluates a hybrid MTCNN–ArcFace framework incorporating centroid-based identity representation, application-specific threshold calibration, and real-time validation for automated student attendance. A quantitative experimental design was conducted using a locally collected dataset from a secondary school. MTCNN was employed for face detection and alignment, whereas ArcFace with a ResNet-50 backbone generated facial embeddings that were aggregated into centroid templates for identity matching. The framework was assessed through offline performance evaluation and operational deployment. The proposed approach achieved 92.86% accuracy, 97.22% precision, 92.86% recall, and a 93.49% F1-score, with a 4.76% false acceptance rate and 2.38% false rejection rate. In addition, centroid representation reduced template storage requirements and supported efficient real-time recognition using limited enrollment samples. These findings demonstrate that centroid-based identity representation enhances the practicality of deep face recognition for educational attendance systems by improving computational efficiency while maintaining reliable recognition performance in authentic school environments.
Co-Authors Abdul Rakhman Abdurrachman Faiz Ade Silvia Handayani Adewasti Adewasti Adewasti Aditia Prathama Aida Syarif Aknes Tasia Pratama Alpha Rabbi Sugara Altrucia Pinem Amperawan Amperawan Bayu Sanjaya Ciksadan Ciksadan Dimas Andreansyah Dina Hervita Eliza Fitri Ramadanti Evelina, Evelina Fatahul Arifin Felisia Talitha Aprilia Hafizh Ulwan Handava Wardana Hesti, Emilia Ihsan Mustaqiim Indri Ariyanti Irma Salamah Isa, Indra Griha Tofik Lindawati Lindawati Lindawati Lusi Risky Faradila M. Ardiansyah Martinus Mujur Rose Masayu Anisah Mila Mila Mohammad Fadhli Muhammad Gian Azzra Ramadhan Nadia Miranda Narita Tria Almirah RD Kusumanto Rizkia Meyliana Rosita Efriyanti Rusdianasari Rusdianasari Sabilal Rasyad Shaffa Shaffa Sholihin Sholihin Siti Fatima Sopian Soim, Sopian Suci Putri Widyani Suroso Suroso Suroso Syanno Revy Widia Salsabila Yanita Fibriliyanti Yohandi Bow