Employee Attendance and Performance Monitoring System with Facial Recognition Technology and Data Analytics

Abstract

Paper-based attendance monitoring is being altered daily, whether in public or private, making it unreliable in evaluating the authenticity of attendance. In a career context, attendance plays a fundamental role, and traditional methods for monitoring it need to be updated. The emergence of biometric identification, particularly facial recognition, offers a promising solution. This study introduces FRaDA, an employee data Analytics with a Face Recognition System developed explicitly for Talisay Elementary School (TES) faculty and staff. The system aims to digitize attendance monitoring and employee evaluation processes by leveraging facial recognition technology. It captures and records attendance via live camera feed, generates efficient performance and attendance reports, minimizes recording errors and tampering, automates Daily Time Records (DTR) generation, and facilitates intensive attendance management. The methodological approach follows the Agile Scrum model and involves Initialization, Planning and Estimating, Implementation, Review, and Releasing phases, ensuring a systematic and efficient development process. Key highlights include the evaluation process with an overall score of 3.00, indicating the project's feasibility and excellence. In conclusion, Project FRaDA offers a practical and efficient solution for attendance management and employee evaluation, addressing the limitations of traditional methods and meeting the institution's needs.