Klasifikasi Absensi Face Geo-Location Menggunakan Metode CNN pada PT Indomarco Prismatama - Mulyana, Dadang Iskandar; Aribatullah (Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh, 2025)
The rapid development of information technology forces companies to continue to improve operational efficiency, including in managing employee attendance. An accurate and efficient attendance system is essential to monitor employee attendance and ensure operational effectiveness. However, traditional attendance using fingerprints still has weaknesses, such as the potential for data manipulation through NIK input without physical presence. This study aims to develop a facial recognition-based attendance system using the Convolutional Neural Network (CNN) method that can ensure employee attendance in real-time. This technology is expected to improve the accuracy and reliability of the attendance system, as well as reduce the potential for fraud. The implementation of this system at PT Indomarco Prismatama, known as the Indomaret retail network, aims to simplify the attendance process for field employees and make it easier for management to monitor employee attendance in various locations.