<![CDATA[The research was motivated by the fact that many higher education institutions still rely on manual attendance methods, which are prone to recording errors, time-consuming, and susceptible to irregularities. To address these issues, a facial recognition-based attendance system was designed using Python as the primary programming language. The system employs an object-oriented programming (OOP) approach to facilitate the development of components such as face detection, student data storage, attendance validation, and report generation. The implemented facial recognition technology enables automated, real-time attendance recording, resulting in greater data accuracy and minimal manual intervention. Furthermore, the system offers rapid and flexible attendance reporting features, making it easier for lecturers and administrative staff to monitor student attendance. Simulation results indicate that the system improves efficiency, accelerates the recording process, and reduces potential irregularities compared to conventional attendance methods.]]>
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