Sistem Absensi Mahasiswa Berbasis Pengenalan Wajah Menggunakan Algoritma YOLOv5
DOI:
https://doi.org/10.30865/jurikom.v10i2.6032Keywords:
Algorithm, Face Recognition, absenteeism, Artificial Intelligence, YOLOv5Abstract
The development of information technology is accompanied by advances in the fieldArtificial Intelligence, one of which is the facial recognition systemmachine learning ordeep learning. When humans see an image or video, we can recognize and find objects of interest in an instant. The goal of object detection is to replicate this intelligence using computers. The student attendance system at Bina Insan Lubuklinggau University is still done manually so it has many deficiencies such as attendance data or signatures that can be manipulated by others, causing fraud. there is a risk of losing data, in the process of inputting data. So that in this study a Student Attendance System was created at the Faculty of Engineering, Bina Insan University Using the YOLO v5 Algorithm. It is hoped that this will be used to obtain appropriate attendance results and there will be no more fraud and the risk of inputting attendance data errors, especially at Bina Insan University, Lubuklinggau City. In this study, 5 class datasets were used in the form of 5 students at the Faculty of Engineering, Bina Insan University. The accuracy results in detecting faces are approximately 80%. From a dataset of approximately 1500 images, with a photo size of 640x640pixel, 16 batch withepoch as many as 100 models will be evaluated by taking into account the values of mAP, Precision, Recall. In this study, the model gets 99% mAP, 99% precision, and 99% recall, with this, the system created is good enough
References
R. P. Arum, A. Prasetiadi, and C. Ramdani, “Klasifikasi Rasa Berdasarkan Citra Buah Menggunakan Algoritma Convolutional Neural Network Dengan Teknik Identitas Ganda,†IJIS - Indones. J. Inf. Syst., vol. 6, no. 1, p. 79, 2021, doi: 10.36549/ijis.v6i1.132.
N. Hanum Harani, C. Prianto, and M. Hasanah, “Deteksi Objek Dan Pengenalan Karakter Plat Nomor Kendaraan Indonesia Menggunakan Metode Convolutional Neural Network (CNN) Berbasis Python,†J. Tek. Inform., vol. 11, no. 3, pp. 47–53, 2019.
W. I. Pambudi, M. Izzatillah, and S. Solikhin, “Sistem Pendukung Keputusan Pemilihan Karyawan Terbaik Menggunakan Metode AHP PT NGK Busi Indonesia,†J. Ris. dan Apl. Mhs. Inform., vol. 2, no. 01, pp. 113–120, 2021, doi: 10.30998/jrami.v2i01.925.
Awan Aprilino and Imam Husni Al Amin, “1522-4565-1-Pb,†J. TEKNOINFO, vol. 16, no. 1, pp. 54–59, 2022.
S. Ilahiyah and A. Nilogiri, “Implementasi Deep Learning Pada Identifikasi Jenis Tumbuhan Berdasarkan Citra Daun Menggunakan Convolutional Neural Network,†JUSTINDO (Jurnal Sist. dan Teknol. Inf. Indones., vol. 3, no. 2, pp. 49–56, 2018.
H. O. K. Sugianto, M. A. D. Widyadara, and A. B. Setiawan, “Implementation of Face Recognition for Attendance Using Yolo V3 Method,†Semin. Nas. Inov. Teknol., vol. 6, no. 2, pp. 50–55, 2022, [Online]. Available: https://proceeding.unpkediri.ac.id/index.php/inotek/article/view/2559.
Y. Hartiwi, E. Rasywir, Y. Pratama, and P. A. Jusia, “Sistem Manajemen Absensi dengan Fitur Pengenalan Wajah dan GPS Menggunakan YOLO pada Platform Android,†J. Media Inform. Budidarma, vol. 4, pp. 1235–1242, 2020, doi: 10.30865/mib.v4i4.2522.
I. Salamah, M. R. A. Said, and S. Soim, “Perancangan Alat Identifikasi Wajah Dengan Algoritma You Only Look Once (YOLO) Untuk Presensi Mahasiswa,†J. Media Inform. Budidarma, vol. 6, no. 3, p. 1492, 2022, doi: 10.30865/mib.v6i3.4399.
N. Hidayat, S. Wahyudi, A. Aufa Diaz, I. Teknologi Sepuluh Nopember, and K. Keputih-Sukolilo, “PENGENALAN INDIVIDU MELALUI IDENTIFIKASI WAJAH MENGGUNAKAN METODE YOU ONLY LOOK ONCE (YOLOv5) (Individual Recognition Through Face Identification Based On You Only Look Once (YOLOv5) Method),†pp. 85–98, 2022, [Online]. Available: https://magestic.unej.ac.id/.
K. Khairunnas, E. M. Yuniarno, and A. Zaini, “Pembuatan Modul Deteksi Objek Manusia Menggunakan Metode YOLO untuk Mobile Robot,†J. Tek. ITS, vol. 10, no. 1, 2021, doi: 10.12962/j23373539.v10i1.61622.
I. N. T. A. Putra and E. D. Krisna, “Implementasi Sistem Surveillance Berbasis Pengenalan Wajah pada STMIK STIKOM Indonesia,†J. Ilmu Komput., vol. 13, no. 2, p. 8, 2020, doi: 10.24843/jik.2020.v13.i02.p01.
A. Amwin, “Deteksi Dan Klasifikasi Kendaraan Berbasis Algoritma You Only Look Once (YOLO),†Univ. Islam Indones., 2021, [Online]. Available: https://dspace.uii.ac.id/handle/123456789/34154.
F. Hardianto, “Aplikasi Presensi Online WFH Menggunakan Sidik Jari Dan Face Recognition Berbasis Mobile (Studi Kasus: PT Toko Damai Sejahtera Kota Rengat),†2022, [Online]. Available: http://repository.uir.ac.id/id/eprint/15659%0Ahttps://repository.uir.ac.id/15659/1/183510046.pdf.
Muhammad Romzi and B. Kurniawan, “Pembelajaran Pemrograman Python Dengan Pendekatan Logika Algoritma,†JTIM J. Tek. Inform. Mahakarya, vol. 03, no. 2, pp. 37–44, 2020.
M. Moshinsky, “No Titleیلیب,†Nucl. Phys., vol. 13, no. 1, pp. 104–116, 1959.
M. S. Hidayatulloh, “Sistem Pengenalan Wajah Menggunakan Metode Yolo ( You Only Look Once ),†pp. i–43, 2021.
I. N. T. A. Putra, “Face Recognition Based Mobile Using Fisherface and Distance Classifier,†JST (Jurnal Sains dan Teknol., vol. 7, no. 1, pp. 135–145, 2018, doi: 10.23887/jst-undiksha.v7i1.13267.
J. Jumadi, Y. Yupianti, and D. Sartika, “Pengolahan Citra Digital Untuk Identifikasi Objek Menggunakan Metode Hierarchical Agglomerative Clustering,†JST (Jurnal Sains dan Teknol., vol. 10, no. 2, pp. 148–156, 2021, doi: 10.23887/jstundiksha.v10i2.33636.
Indrasetya, Sugeng, and Putri, “Penerapan Yolo Dalam Konversi Partitur Lagu Dari Notasi Balok Menjadi Notasi Angka,†pp. 1–12, 2021, [Online]. Available: https://eproceeding.itenas.ac.id/index.php/fti/article/view/586%0Ahttps://eproceeding.itenas.ac.id/index.php/fti/article/download/586/478.
M. I. Siami, “Penerapan Deteksi Penggunaan Masker pada Sistem Absensi Karyawan menggunakan Metode Deep Learning,†JAMI J. Ahli Muda Indones., vol. 3, no. 2, pp. 21–27, 2022, doi: 10.46510/jami.v3i2.118.
