<![CDATA[Attendance is one of the important aspects in managing the presence of employees and students. Manual or card-based attendance methods still have several weaknesses, such as being prone to manipulation, requiring more time, and lacking efficiency. Therefore, this study develops a prototype of a real-time face recognition-based attendance system using Python and OpenCV. The research method applied is Prototyping, consisting of stages of requirement analysis, system design,implementation, and testing. The system is designed using the Haar Cascade algorithm for face detection and Local Binary Pattern Histogram (LBPH) for face recognition. The database uses SQLite with three main tables: users, positions, and attendance. The system was tested using four face datasets with a total of approximately 400 images, namely from users: Ronaldo, Lisra, Juliardo, and Riswanti. The test results show that the system can detect and recognize users' faces in real-time, automatically record attendance, and generate daily, monthly, and individual attendance reports.]]>
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