SISTEM ABSENSI MOBILE BERBASIS FACE RECOGNITION DAN GEOFENCING
DOI:
https://doi.org/10.35145/jmapteksi.v8i2.6020Kata Kunci:
CNN, Face Recognition, Geofencing, Aplikasi Mobile, Sistem AbsensiAbstrak
Pencatatan kehadiran karyawan secara manual masih menjadi permasalahan umum di banyak perusahaan, termasuk PT Andika Mitra Anugerah Pekanbaru. Sistem berbasis kertas maupun spreadsheet yang digunakan saat ini tidak mampu mencegah manipulasi data kehadiran dan tidak memiliki mekanisme validasi lokasi yang memadai. Penelitian ini bertujuan merancang dan mengimplementasikan sistem absensi mandiri berbasis mobile yang mengintegrasikan teknologi Face Recognition dengan algoritma Convolutional Neural Network (CNN) dan mekanisme Geofencing berbasis rumus Haversine. Sistem dibangun menggunakan Flutter untuk antarmuka mobile karyawan, PHP dan MySQL untuk backend server, serta Android Studio sebagai lingkungan pengembangan. Tingkat kemiripan wajah dihitung menggunakan rumus Cosine Similarity dengan ambang batas threshold sebesar 0,8. Hasil pengujian pada enam skenario menunjukkan skor kemiripan antara 0,81–0,94 untuk wajah asli, sekaligus menolak manipulasi foto cetak (skor 0,34) dan wajah asing (skor 0,12). Pengujian Black Box pada tujuh modul menghasilkan status berhasil di seluruh skenario. Evaluasi kuesioner terhadap lima responden menghasilkan skor rata-rata 64% (kategori "Baik", Sugiyono 2021). Sistem terbukti mampu menggantikan proses absensi manual dengan solusi yang lebih aman, akurat, dan efisien.
Unduhan
Referensi
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