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All Journal Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi)
Lintang Bagas Adrianto
Program Studi Informatika, Fakultas Teknologi Komunikasi dan Informatika, Universitas Nasional
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

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Implementasi Deep Learning untuk Sistem Keamanan Data Pribadi Menggunakan Pengenalan Wajah dengan Metode Eigenface Berbasis Android Lintang Bagas Adrianto; Mohammad Iwan Wahyuddin; Winarsih Winarsih
Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi) Vol 5 No 1 (2021): JANUARI-MARET 2021
Publisher : KITA Institute

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35870/jtik.v5i1.201

Abstract

The development of technology in security systems combined with facial recognition, of course, makes every protected data safe. Many methods can be combined with a security system, one of which is the eigenface method, which is part of facial recognition. In this study, a personal data security system was built using Android-based deep learning. Based on the results of tests carried out on three devices with different Android versions, it is known, if on Android 8.1 (Oreo) the maximum distance is ± 40 cm, on Android 9.0 (Pie) the maximum distance is ± 50 cm, and on the Android version, 10.0 (Q) the maximum distance for facial object recognition is ± 60 cm. From the test results, it is known that by using the eigenface method, the farther the face is from the camera, the face cannot be detected. The implementation of this system is expected to protect personal data safely.
Co-Authors Mohammad Iwan Wahyuddin Winarsih Winarsih