Sistem Keamanan Perumahan Menggunakan Face Recognition


  • Desi Ramayanti * Mail Universitas Dian Nusantara, Jakarta, Indonesia
  • Yuwan Jumaryadi Universitas Mercu Buana, Jakarta, Indonesia
  • Daim Muhammad Gufron Universitas Mercu Buana, Jakarta, Indonesia
  • Dio Dava Ramadha Universitas Mercu Buana, Jakarta, Indonesia
  • (*) Corresponding Author
Keywords: Android Application; Security System; Face Recognition

Abstract

The residential environment system is a system that can be used to assist security officers and neighborhood residents to carry out environmental monitoring of crimes both coming from outside the environment and from the environment itself. This residential security system application uses the face recognition method carried out by residential security. The security system is an important point, which makes it the most important goal of researchers. Data collection methods used such as, observation, observation and literature study. The results of this study are to create a security system application using android-based facial recognition. The conclusion of this research is that this residential security system application is designed with simple systems and features to make it easier for users or users, with the Face Recognition method it makes it easier for security guards to carry out security for people who come out of housing, and the security system application is an application designed to help community and security officers so as not to lose the motorized vehicles of residential residents

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References

Ayumi, V., & Dwika Putra, E. (2020). Pengenalan Gerak Manusia Menggunakan Algoritma Relevance Vector Machine pada MSRC-12 Dataset. JSAI (Journal Scientific and Applied Informatics), 3(1), 49–52. https://doi.org/10.36085/jsai.v3i1.850

Ayumi, V., Nurhaida, I., & Noprisson, H. (2022). Implementation of Convolutional Neural Networks for Batik Image Dataset. International Journal of Computing Science and Applied Mathematics, 8(1), 5. https://doi.org/10.12962/j24775401.v8i1.5053

Ben Ayed, M., Elkosantini, S., Alshaya, S. A., & Abid, M. (2019). Suspicious Behavior Recognition Based on Face Features. IEEE Access, 7, 149952–149958. https://doi.org/10.1109/ACCESS.2019.2947338

Capote-Leiva, J., Villota-Rivillas, M., & Muñoz-Ordóñez, J. (2022). Access Control System based on Voice and Facial Recognition Using Artificial Intelligence. International Journal on Advanced Science, Engineering and Information Technology, 12(6), 2342–2348. https://doi.org/10.18517/ijaseit.12.6.16049

Chyan, P., Syarif, A. C., Sumarta, S. C., & Daromes, F. E. (2018). Desain Model Sistem Keamanan Berbasis Kamera Dengan Image Enhancement Algorithm. Jurnal Riset Komputer (JURIKOM), 5(4), 390–396.

Hidayatullah, A., & Putra, Y. A. (2022). Perancangan Sistem Keamanan Perumahan Menggunakan Face Recognition Berbasis Android. Arcitech: Journal Pf Computer Science and Artificial Intelligence, 2(2), 87–102.

Mutezar, A. A., & Umniy Salamah. (2021). Pengembangan Sistem Manajemen Event Pameran Karya Mahasiswa Menggunakan Metode Extreme Programming. Jurnal RESTI (Rekayasa Sistem Dan Teknologi Informasi), 5(4), 809–819. https://doi.org/10.29207/resti.v5i4.3249

Prasetyo, T. F., Zaliluddin, D., & Iqbal, M. (2018). Prototype of smart office system using based security system. Journal of Physics: Conference Series, 1013(1). https://doi.org/10.1088/1742-6596/1013/1/012189

Priambodo, B., & Jumaryadi, Y. (2022). Sistem Pakar Deteksi Covid-19 Dengan Lie Detection Menggunakan Metode Circle Hough Transform. Journal of Computer System and Informatics (JoSYC), 4(1), 238–244. https://doi.org/10.47065/josyc.v4i1.2528

Provinsi DKI Jakarta, B. (2023). Jumlah Kejahatan/Pelanggaran Kamtibnas Menurut Jenis dan Kabupaten/Kota Administrasi 2017-2020. Badan Pusat Statistik Provinsi DKI Jakarta. https://jakarta.bps.go.id/indicator/27/580/1/jumlah-kejahatan-pelanggaran-kamtibnas-menurut-jenis-dan-kabupaten-kota-administrasi-2018.html

Purwawijaya, E., Singarimbun, R. N., & Pasaribu, H. (2022). Implementasi Face Recognition Pada Absensi Karyawan Menggunakan Local Binary Pattern Histogram dan SHA 256 bit. Jurnal Media Informatika Budidarma, 6(4), 2383. https://doi.org/10.30865/mib.v6i4.4923

Stergiou, C. L., Bompoli, E., & Psannis, K. E. (2023). Security and Privacy Issues in IoT-Based Big Data Cloud Systems in a Digital Twin Scenario. Applied Sciences (Switzerland), 13(2). https://doi.org/10.3390/app13020758


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