<![CDATA[Attendance tracking for teachers and students at biMBA AIUEO Klender Unit is currently conducted manually using paper forms, rendering the process susceptible to physical document loss and time manipulation through timestamp camera applications. This conventional approach also poses compliance risks regarding Government Regulation Number 17 of 2025 and Minister of Communication and Digital Affairs Regulation Number 9 of 2026 concerning electronic system governance in child protection. This study aims to design and develop a web-based attendance system that integrates facial recognition technology to prevent fraudulent teacher attendance, while ensuring that student attendance records remain entirely under the supervision and operational authority of teacher accounts. The system was developed using the Agile software engineering framework, combined with qualitative data collection through observation, interviews, and literature study, alongside quantitative descriptive evaluation [cek metode: if the journal explicitly requires the term 'numerical method', replace with: alongside numerical quantitative evaluation] to determine the validity rates of Black-box Testing and user satisfaction levels via User Acceptance Testing. The application was constructed using Laravel, PHP 8.2+, and MySQL, enhanced with geofencing verification, automated WhatsApp Gateway notifications, DOMPDF-based report generation, and Progressive Web App accessibility. Black-box Testing demonstrated that all 18 test scenarios were completely valid (100%), while User Acceptance Testing across user categories achieved an overall average score of 91.6%, categorized as "Very Good." This study confirms that the proposed system effectively eliminates attendance manipulation loopholes, complies with statutory child protection regulations, and improves administrative monitoring and reporting efficiency for biMBA AIUEO Klender Unit.]]>
Copyrights © 2026
