Manual attendance at MA Sabilil Mukarromah is vulnerable to proxy attendance, data inaccuracies, and delayed information for parents. This study develops a web-based student attendance system with WhatsApp Gateway notifications using the Waterfall method, Laravel PHP, MySQL, face-api.js, Geolocation API, and Fonnte API. The system supports five user roles (admin, teacher, homeroom teacher, student, and parent) with layered validation via GPS geolocation and face recognition. Notifications are sent in real-time for each attendance event, including digital permission requests and alpha sanctions management. Black box testing of 14 components confirmed all scenarios produced expected results without errors. Face recognition testing on 6 students achieved 83.3% accuracy, with failures only under low light conditions. The WhatsApp Gateway achieved a 66.7% delivery rate with an average latency of 5 seconds, supporting more effective, accurate, and transparent attendance management.
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