Absensi Pengenalan Wajah Menggunakan Menggunakan Algoritma Eigenface Berbasis Web
Abstract
During the Covid-19 virus pandemic as it is currently being experienced in Indonesia is very rapidly spreading, forcing the government to impose a PSBB (Pembatasan Sosial Bersekala Besar) system in several regions in Indonesia. With the government regulation on health protocols, many companies must take action to minimize the spread of the Covid-19 virus. In this situation with daily activities opens opportunities for the Covid-19 virus to spread very quickly, especially in the office sphere. The spread of the Covid-19 virus could be through an attendance system that still uses finger print tools used to collect employee attendance data. In this study, attendance application developed using facial recognition method as key for employee data retrieval. This method of facial recognition is applied in real time with a certain distance and lighting. Eigenface algorithm is used as a training process for employees' faces that have been inputted before. The results of the training data will be saved to a database which is then used as a key to recognize the faces of employees who will perform attendance. In the results of the trial the attendance data application will enter when the level of facial recognition is above 70%.
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References
M. R. Muliawan, B. Irawan, and Y. Brianorman, “Implementasi Pengenalan Wajah DenganMetode Eigenface Pada Sistem Absensi,” Jurnal Coding, Sistem Komputer Untan, vol. 03, no. 1, pp. 41–50, 2015.
I. Abdussalam, A. Rizal, and S. Aulia, “Desain dan realisasi sistem pendeteksi wajah untuk absensi karyawan dengan metode 2d-dct dan pca menggunakan webcam,” 2012.
M. W. Septyanto, H. Sofyan, H. Jayadianti, O. S. Simanjuntak, and D. B. Prasetyo, “Aplikasi Presensi Pengenalan Wajah Dengan Menggunakan Algoritma Haar Cascade Classifier,” Telematika: Jurnal Informatika dan Teknologi Informasi, vol. 16, no. 2, pp. 87–96, 2020.
M. Arsal, B. Agus Wardijono, and D. Anggraini, “Face Recognition Untuk Akses Pegawai Bank Menggunakan Deep Learning Dengan Metode CNN,” J. Teknol. dan Sist. Inf., vol. 6, no. 1, pp. 55–63, 2020.
M. W. Septyanto, H. Sofyan, H. Jayadianti, O. S. Simanjuntak, and D. B. Prasetyo, “Aplikasi Presensi Pengenalan Wajah Dengan Menggunakan Algoritma Haar Cascade Classifier,” Telematika: Jurnal Informatika dan Teknologi Informasi, vol. 16, no. 2, pp. 87–96, 2020.
D. E. Kurniawan, K. Adi, and A. F. Rohim, “Sistem Identifikasi Biometrika Wajah Menggunakan Metode Gabor KPCA dan Mahalanobis Distance,” J. SIST. INF. BISNIS, vol. 2, no. 1, 2014.
D. I. Bramantio, “Perancangan Dan Implementasi Keamanan Pintu Berbasis Pengenalan Wajah Dengan Metode Eigenface,” tektrika, vol. 1, no. 2, 2019.
N. W. Marti, “Pemanfaatan gui dalam pengembangan perangkat lunak Pengenalan citra wajah manusia menggunakan metode Eigenfaces,” 2010.
S. Salamun and F. Wazir, “Rancang Bangun Sistem Pengenalan Wajah Dengan Metode Principal Component Analysis,” rabit, vol. 1, no. 2, pp. 59–75, 2016.
S. Subiantoro and S. Sardiarinto, “Perancangan Sistem Absensi Pegawai Berbasis Web Studi Kasus: Kantor Kecamatan Purwodadi,” Swabumi, vol. 6, no. 2, 2018.
D. Suprianto and R. N. Hasanah, “Sistem Pengenalan Wajah Secara Real-Time dengan Adaboost, Eigenface PCA & MySQL,” Jurnal Eeccis, vol. 7, no. 2, pp. 179–184, 2014.
S. R. Wurdianarto, S. Novianto, and U. Rosyidah, “Perbandingan euclidean distance dengan canberra distance pada face recognition,” Techno. Com, vol. 13, no. 1, pp. 31–37, 2014.
D. E. Kurniawan, and A. Dzikri, "Pengenalan Personal Berdasarkan Pengukuran Jarak Citra Wajah Menggunakan Pendekatan Linear dan Nonlinear," SNTIK 2015
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