Face Recognition-Based Teacher Attendance System Using the Haar Cascade Classifier Method
-
Zeinor Rahman
*
University of KH. Bahaudin Mudhary Madura, Sumenep,
Indonesia
- Ali Fikri University of KH. Bahaudin Mudhary Madura, Sumenep, Indonesia
- Rizki Anantama University of KH. Bahaudin Mudhary Madura, Sumenep, Indonesia
- Mohammad Iqbal Bachtiar University of KH. Bahaudin Mudhary Madura, Sumenep, Indonesia (*) Corresponding Author
Abstract
The teacher attendance process at Madrul Muttaqien Madrasah Diniyah is still conducted conventionally, creating the potential for recording errors and attendance data manipulation. This study develops an automated attendance application based on image processing to detect and recognize faces. The face detection process utilizes the Haar Cascade Classifier method, while face recognition is performed using the Local Binary Patterns Histograms (LBPH) method. System performance was evaluated through two testing scenarios: (1) a recall test involving 15 facial samples under various conditions, including shadow-covered faces, low-light environments, and tilted head positions, which achieved a recall value of 100%; and (2) a distance test conducted at distances of 40.27 cm, 57.69 cm, 63.16 cm, and 70 cm. The system successfully detected and recognized faces with a recall value of 100% at distances up to 63.16 cm but failed to recognize faces at a distance of 70 cm. These results indicate that the application is highly reliable under challenging lighting and orientation conditions and remains effective at distances of up to approximately 63 cm, beyond which its detection capability decreases significantly
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References
S. Sharma and R. Kumar, “Face Recognition-Based Attendance System Using LBPH Algorithm,” International Journal of Advanced Computer Science and Applications, vol. 12, no. 4, pp. 123–129, 2021.
A. Verma and P. Singh, “Implementation of Face Recognition Attendance System Using OpenCV,” International Journal of Computer Applications, vol. 174, no. 15, pp. 10–16, 2021.
M. A. Rahman, M. Islam, and S. Hossain, “Automatic Attendance System Using Haar Cascade and LBPH Face Recognition,” Journal of Information Systems Engineering and Business Intelligence, vol. 8, no. 2, pp. 95–104, 2022.
A. Pratama and B. Nugroho, “Implementation of Face Recognition Technology for Academic Attendance Monitoring,” International Journal of Informatics and Communication Technology, vol. 11, no. 1, pp. 44–53, 2022.
N. Gupta and S. Mishra, “Real-Time Face Detection and Recognition for Smart Attendance Systems,” International Journal of Engineering Research and Technology, vol. 11, no. 5, pp. 321–328, 2022.
R. Kurniawan, A. F. Rochim, and K. T. Martono, “Face Recognition-Based Attendance Application Using Local Binary Pattern Histogram,” Jurnal Teknologi dan Sistem Komputer, vol. 11, no. 1, pp. 1–8, 2023.
H. Zhang and Y. Li, “Comparative Analysis of Face Recognition Methods for Attendance Applications,” IEEE Access, vol. 11, pp. 55421–55433, 2023.
M. S. Hidayat and A. Setiawan, “Implementation of Haar Cascade Classifier for Face Detection in Attendance Systems,” Journal of Physics: Conference Series, vol. 2453, no. 1, pp. 1–8, 2023.
D. R. Sari and E. W. Pamungkas, “Development of Face Recognition Attendance System Using OpenCV and Python,” International Journal of Artificial Intelligence Research, vol. 7, no. 2, pp. 80–89, 2023.
S. Lee and J. Kim, “Efficient Face Recognition System for Educational Attendance Monitoring,” Sensors, vol. 24, no. 3, pp. 1–18, 2024.
A. K. Das, P. Roy, and S. Dutta, “Performance Evaluation of LBPH-Based Face Recognition under Different Lighting Conditions,” IEEE Access, vol. 12, pp. 10215–10228, 2024.
M. F. Arifin and T. Harjono, “Face Recognition-Based Attendance System Using Haar Cascade and LBPH Methods,” Journal of Information Technology and Computer Science, vol. 9, no. 1, pp. 15–24, 2024.
Y. Wang, X. Zhao, and H. Liu, “Robust Face Recognition for Smart Attendance Applications,” Expert Systems with Applications, vol. 245, pp. 1–14, 2025.
R. A. Putra, D. H. Wibowo, and S. Nurhayati, “Evaluation of Face Recognition Accuracy in Educational Attendance Systems,” Indonesian Journal of Electrical Engineering and Computer Science, vol. 35, no. 2, pp. 567–575, 2025.
F. Rahmawati and A. Syahputra, “Implementation of Computer Vision-Based Attendance System Using Haar Cascade Classifier,” International Journal of Advanced Technology and Engineering Exploration, vol. 12, no. 115, pp. 120–129, 2025.
S. Gupta and K. Sharma, “Implementation of Face Recognition for Smart Attendance System Using OpenCV,” International Journal of Engineering Research and Technology, vol. 11, no. 5, pp. 452–458, 2022.
M. A. Rahman, M. Islam, and S. Hossain, “Automated Attendance Management System Using Facial Recognition,” Journal of Information Systems Engineering and Business Intelligence, vol. 8, no. 2, pp. 115–124, 2022.
R. Kumar and A. Sharma, “Real-Time Face Recognition Attendance System Using Haar Cascade and LBPH Algorithms,” International Journal of Innovative Technology and Exploring Engineering, vol. 12, no. 1, pp. 67–74, 2023.
S. Z. Li, A. K. Jain, and J. Deng, Handbook of Face Recognition, 3rd ed. Cham, Switzerland: Springer, 2024.
T. Bourlai, Face Recognition Across the Imaging Spectrum, 2nd ed. Singapore: Springer, 2024.
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Copyright (c) 2026 Zeinor Rahman, Ali Fikri, Rizki Anantama, Mohammad Iqbal Bachtiar
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