Implementasi Deep Learning untuk Sistem Keamanan Data Pribadi Menggunakan Pengenalan Wajah dengan Metode Eigenface Berbasis Android

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Lintang Bagas Adrianto
Mohammad Iwan Wahyuddin
Winarsih Winarsih

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.

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How to Cite
Adrianto, L. B., Wahyuddin, M. I., & Winarsih, W. (2021). Implementasi Deep Learning untuk Sistem Keamanan Data Pribadi Menggunakan Pengenalan Wajah dengan Metode Eigenface Berbasis Android. Jurnal JTIK (Jurnal Teknologi Informasi Dan Komunikasi), 5(1), 89–96. https://doi.org/10.35870/jtik.v5i1.201
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