The Office Room Security System Using Face Recognition Based on  Viola-Jones Algorithm and RBFN

Andree E. Widjaja; Hery Hery; David Habsara Hareva

doi:10.29407/intensif.v5i1.14435

Authors

Andree E. Widjaja Universitas Pelita Harapan https://orcid.org/0000-0002-3112-9662
Hery Hery Universita Pelita Harapan https://orcid.org/0000-0001-6483-0511
David Habsara Hareva Universitas Pelita Harapan

DOI:

https://doi.org/10.29407/intensif.v5i1.14435

Keywords:

Office Security, Face Recognition, Prototyping, Database

Abstract

The university as an educational institution can apply technology in the campus environment. Currently, the security system for office space that is integrated with digital data has been somewhat limited. The main problem is that office space security items are not guaranteed as there might be outsiders who can enter the office. Therefore, this study aims to develop a system using biometric (face) recognition based on Viola-Jones and Radial Basis Function Network (RBFN) algorithm to ensure office room security. Based on the results, the system developed shows that object detection can work well with an object detection rate of 80%. This system has a pretty good accuracy because the object matching success is 73% of the object detected. The final result obtained from this study is a prototype development for office security using face recognition features that are useful to improve safety and comfort for occupants of office space (due to the availability of access rights) so that not everyone can enter the office.

Downloads

Download data is not yet available.

References

L. Lestary and H. Harmon, “Pengaruh Lingkungan Kerja Terhadap Kinerja Karyawan,” J. Ris. Bisnis dan Investasi, 2018, doi: 10.35697/jrbi.v3i2.937.

I. A. Dianta and E. Zusrony, “Analisis Pengaruh Sistem Keamanan Informasi Perbankan pada Nasabah Pengguna Internet Banking,” INTENSIF, 2019, doi: 10.29407/intensif.v3i1.12125.

R. Umar, I. Riadi, and E. Handoyo, “Analisis Keamanan Sistem Informasi Berdasarkan Framework COBIT 5 Menggunakan Capability Maturity Model Integration (CMMI),” J. Sistem Informasi Bisnis, 2019, doi: 10.21456/vol9iss1pp47-54.

A. Setiawan and A.E. Purnamasari, “Pengembangan Smart Home dengan Microcontrollers ESP32 dan MC-38 Door Magnetic Switch Sensor Berbasis Internet of Things (IoT) Untuk Meningkatkan Deteksi Dini Keamanan Perumahan,” J. Rekayasa Sistem dan Teknologi Informasi, 2019, doi: 10.29207/resti.v3i3.1238.

A. Kurniawan, “Digital Rights Management Sebagai Solusi Keamanan Dokumen Elektronik,” J. Sistem Informasi, 2012, doi:10.21609/jsi.v4i2.251.

S. Widodo, E. Sediyono, and Suhartono, “Desain Sistem Keamanan Distribusi Data Dengan Menerapkan XML Encryption dan XML Signature Berbasis Teknologi Web Service,” J. Sistem Informasi Bisnis, 2011, doi: 10.21456/vol1iss1pp47-57.

E. Yuliza and T. U. Kalsum, “Alat Keamanan Pintu Brankas Berbasis Sensor Sidik Jari Dan Password Digital Dengan Menggunakan Mikrokontroler Atmega 16,” J. Media Infotama, 2015, doi: 10.37676/jmi.v11i1.247.

L. Louis, "Working Principle of an Arduino and Using It," Int. J. Control. Autom. Commun. Syst., 2016, doi: 10.5121/ijcacs.2016.1203.

N. David, A. Chima, A. Ugochukwu, and E. Obinna, “Design of a Home Automation System Using Arduino,” Int. J. Sci. Eng. Res., 2015.

M. K. Syabibi and A. Subari, “Rancang Bangun Sistem Monitoring Keamanan Rumah Berbasis Web Menggunakan Raspberry Pi B+ Sebagai Server Dan Media Kontrol,” Gema Teknol., vol. 19, no. 1, p. 22, 2016, doi: 10.14710/gt.v19i1.21959.

M. Arihutomo, A. Budikarso, and Setiawardhana, “Rancang Bangun Sistem Penjejakan Objek Menggunakan Metode Viola Jones Untuk Aplikasi Eyebot,” EEPIS Final Proj., 2010, Accessed: Nov. 02, 2016. [Online]. Available: http://repo.pens.ac.id/id/eprint/311.

Y. Yuliana and I. Nurhaida, “Rancang Bangun Aplikasi Pengenalan Wajah menggunakan Metode Viola-Jones dan Algoritma PCA,” J. Telekomun. dan Komput., 2018, doi: 10.22441/incomtech.v8i3.3385.

D. E. Kurniawan, K. Adi, and A.F. Rohim, “Sistem Identifikasi Biometrika Wajah Menggunakan Metode Gabor KPCA dan Mahalanobis Distance,” J. Sistem Informasi Bisnis, 2014, doi: 10.21456/vol2iss1pp006-010.

N. Saubari, R. Isnanto, and K. Adi, “Jaringan Syaraf Tiruan Perambatan Balik untuk Pengenalan Wajah,” J. Sistem Informasi Bisnis, 2016, doi: 10.21456/vol6iss1pp30-37.

I K. S. Widiakumara, I K. G. D. Putra, and K. S. Wibawa, “Aplikasi Identifikasi Wajah Berbasis Androdi,” J. Ilmiah Teknologi Informasi, 2017, doi:10.24843/LKJITI.2017.v08.i03.p06.

N. Vd. Lima, L. Novamizanti, and E. Susatio, “Sistem Pengenalan Wajah 3D Menggunakan ICP dan SVM,” J. Teknologi Informasi dan Ilmu Komputer, 2019, doi: 10.25126/jtiik.2019661609.

R. Wiryadinata, U. Istiyah, R. Fahrizal, Priswanto, and S. Wardoyo, “Sistem Presensi Menggunakan Algoritma Eigenface dengan Deteksi Aksesoris dan Ekspresi Wajah”, J. Nasional Teknik Elektro dan Teknologi Informasi, 2017, doi: 10.22146/jnteti.v6i2.319.

M. R. Hidayat, C. Christiano, and B. S. Sapudin, "IoT-Based Home Security System Design Using NodeMCU ESP8266, HC-SR501, PIR Sensor AND Smoke Detector Sensor," Kilat, 2018, doi: 10.33322/kilat.v7i2.357.

A. Aileen, Hery, A. E. Widjaja, J. T. Purba, and K. G. Simanjuntak, “Recording application with managerial prediction features for skenoo business,” in IOP Conference Series: Materials Science and Engineering, 2019, doi: 10.1088/1757-899X/508/1/012133.

M. Chaudhari, S. sondur, and G. Vanjare, "A review on Face Detection and study of Viola-Jones method," Int. J. Comput. Trends Technol., 2015, doi: 10.14445/22312803/ijctt-v25p110.

J. Wang, B. Wang, Y. Zheng, and W. Liu, “Research and implementation on face detection approach based on cascaded convolutional neural networks,” in Proceedings - 2017 International Conference on Vision, Image and Signal Processing, ICVISP 2017, 2017, vol. 2017-Novem, pp. 34–39, doi: 10.1109/ICVISP.2017.10.

K. Ganapathy, V. Vaidehi, and J. B. Chandrasekar, "Optimum steepest descent higher-level learning radial basis function network," Expert Syst. Appl., 2015, doi: 10.1016/j.eswa.2015.06.036.

S. Lukas, A. R. Mitra, R. I. Desanti, and D. Krisnadi, "Student attendance system in the classroom using face recognition technique," 2016 International Conference on Information and Communication Technology Convergence, ICTC 2016, 2016, doi: 10.1109/ICTC.2016.7763360.