This study designed and evaluated an Android-based e-attendance application integrating facial biometric verification and WhatsApp notifications to address inefficiencies in manual attendance at MTsN 2 Payakumbuh, Indonesia. A design-and-development methodology using the Spiral Software Development Life Cycle (SDLC) was applied from May to November 2025, covering iterative requirements elicitation (observation and semi-structured interviews), planning, risk analysis with UML modelling, engineering, deployment, and customer evaluation. The system comprises a Laravel–MySQL web dashboard for administrators and a Flutter Android application for teachers. Attendance is verified through Face++ facial recognition, while parents receive automated attendance-status messages via a WhatsApp API. Product quality was assessed through expert validity testing (Aiken’s V), user-practicality testing (Kappa Moment), and a one-group pre-test–post-test effectiveness evaluation (normalized gain). Results indicate high validity for both content and construct dimensions (mean = 0.97), very high practicality (κ = 0.91), and very high effectiveness with substantial improvement from pre-test (33.94%) to post-test (95.15%), yielding g = 0.92. These findings suggest the proposed solution is feasible for routine classroom use, improves administrative efficiency and transparency, and strengthens parent–school communication, while highlighting the need for broader trials and stronger long-term biometric governance. The design includes manual status adjustment and report export to Excel, supporting continuity during connectivity fluctuations common in typical resource-limited schools.
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