PENERAPAN PENGENALAN WAJAH PADA APLIKASI PRESENSI SISWA BERBASIS MOBILE DENGAN NOTIFIKASI LANGSUNG ORANG TUA - Arrahma, Regita Cahya; Asriningtias, Yuli (Jusikom : Jurnal Sistem Komputer Musirawas, 2025)
Manual attendance methods are prone to data loss, delayed recap, and misrecording. This study designs and implements a mobile attendance application based on face recognition with notifications to parents. The system is built with Flutter, Google Machine Learning (ML) Kit for face identification, Firebase Firestore for data storage, and Gmail Simple Mail Transfer Protocol (SMTP) for email delivery. The application was developed using the Waterfall method and verified through black-box testing. The results show that the main features real-time face attendance, attendance time restrictions, attendance logging, and automatic notifications operate according to specifications. This improves data accuracy, transparency of reporting to parents, and the work efficiency of homeroom teachers compared to manual methods. These findings support the feasibility of implementing face recognition in elementary schools while maintaining data privacy and security.