Authors :
Acain Jay Ronel ; Ablayon Anthony ; Manaligod Christian ; Manrique Lorenz Greg ; Morga Arcadio ; Cedie E. Gabriel ; Reginald S. Prudente
Volume/Issue :
Volume 10 - 2025, Issue 5 - May
Google Scholar :
https://tinyurl.com/3msyt7p8
DOI :
https://doi.org/10.38124/ijisrt/25may648
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Abstract :
This research project focuses on improving the SEAIT OJT Monitoring System by integrating face recognition
technology to enhance usability and accessibility. Traditional methods of tracking On-the-Job Training (OJT) attendance
are often time-consuming and prone to errors. By implementing a face recognition system, the project aims to automate
attendance tracking, reduce human errors, and increase security. The study evaluates the system's performance through
usability testing, measuring metrics like accuracy, efficiency, and user satisfaction. Results indicate that the system simplifies
attendance monitoring, provides real-time data, and improves overall user experience. However, challenges such as
environmental factors and device compatibility were noted. The project demonstrates the potential of face recognition
technology to streamline administrative tasks in educational settings while emphasizing the need for further improvements
in accessibility and reliability.
Keywords :
Face Recognition, OJT Monitoring, Usability, Human-Computer Interaction (HCI).
References :
- Anshari, A., Hirtranusi, S. A., Sensuse, D., Kautsarina, K., & Suryono, R. R. (2021). Face Recognition for Identification and Verification in Attendance System: A Systematic Review
- https://www.researchgate.net/publication/354517561_Face_Recognition_for_Identification_and_Verification_in_Attendance_System_A_Systematic_Review
- Ghorpade, Y., Thakare, H., Sonawane, S., Dedhia, A., & Mathur, S. M. (2024). Face Recognition Attendance Monitoring System
- https://www.semanticscholar.org/paper/Face-Recognition-Attendance-Monitoring-System-Ghorpade-Thakare/3de0c7b7141f7d92a6f5d54e0370dc8edd966323
- Gulati, S., McDonagh, J., Sousa, S., & Lamas, D. (2024) Trust models and theories in human–computer interaction: A systematic literature review
- https://www.sciencedirect.com/science/article/pii/S2451958824001283
This research project focuses on improving the SEAIT OJT Monitoring System by integrating face recognition
technology to enhance usability and accessibility. Traditional methods of tracking On-the-Job Training (OJT) attendance
are often time-consuming and prone to errors. By implementing a face recognition system, the project aims to automate
attendance tracking, reduce human errors, and increase security. The study evaluates the system's performance through
usability testing, measuring metrics like accuracy, efficiency, and user satisfaction. Results indicate that the system simplifies
attendance monitoring, provides real-time data, and improves overall user experience. However, challenges such as
environmental factors and device compatibility were noted. The project demonstrates the potential of face recognition
technology to streamline administrative tasks in educational settings while emphasizing the need for further improvements
in accessibility and reliability.
Keywords :
Face Recognition, OJT Monitoring, Usability, Human-Computer Interaction (HCI).
