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Journal : JOINCS (Journal of Informatics, Network, and Computer Science)

Development of an Automated Attendance System Based on Facial Recognition Using Convolutional Neural Networks (CNN) for Kaca Super Jaya MSME: Pengembangan Sistem Kehadiran Otomatis Menggunakan Pengenalan Wajah Menggunakan Convolutional Neural Network (CNN) terhadap UMKM Kaca Super Jaya Syaeful Anas Aklani; Jetset; Suwarno Suwarno
JOINCS (Journal of Informatics, Network, and Computer Science) Vol. 9 No. 1 (2026): April
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21070/joincs.v9i1.1692

Abstract

Attendance management is a critical component of human resource administration, yet conventional methods such as manual sign-in sheets and card-based systems are often inefficient, error-prone, and vulnerable to manipulation. This study aims to design and implement an automatic attendance system based on face recognition using Convolutional Neural Networks (CNN) for UMKM Kaca Super Jaya. The proposed system replaces manual attendance by enabling real-time, contactless, and automated attendance recording through facial identification. An applied research approach with qualitative methods was employed, involving system development, direct observation, and structured interviews with users. The CNN model was trained using facial image datasets under various conditions, including different lighting levels, facial expressions, and viewing angles, to improve robustness and accuracy. The system architecture integrates a camera as input, a CNN-based face recognition model, a backend server, and a web-based dashboard for attendance monitoring and reporting. Experimental results show that the system achieved an average face recognition accuracy of 96%, demonstrating reliable performance even under suboptimal lighting and non-frontal face angles. The implementation significantly reduced attendance processing time, minimized human error, and lowered the potential for fraudulent practices such as proxy attendance. These findings indicate that CNN-based face recognition is an effective and practical solution for enhancing attendance management efficiency and accuracy in small and medium enterprises.
Co-Authors Aldovanda Haflah Setiawan Alex Setiawan Aliefazlea, Qanaya Dherryl Anderson, Atnan Ari Anson Anson Basiron, Halizah Chadric, Felix Charles, Kevin Christina, Lidya Daniel Lim David David Dayton Dayton Delvin Jason Derwin Galen DESI RENATA SINURAT DESI Diana Rose, Felicia Dr. Hendi Sama, S.Kom., M.M.e-Business. Edwin Charley Eka Sucipto Elia, Elia Elvert Elvert Eric Lau Erlina Erlina Erwin Erwin Eryc, Eryc Felix Favian Felix, Ivan Fernando Jose Firmansyah, Muhamad Dody Francisco, Francisco Franky Chainoor Johari Haeruddin Haeruddin Haeruddin, . Haslim, Sartika Dewi Hendi Sama Hertianto Hertianto Hosse Fernando Irawan, Calvianthieno Ivan Felix Jacky Jacky Jacky, Jacky Jason Aaron Yang Jenary Randa Liling Jenry Winata Jesselyn Jesslyn, Jesslyn Jetset Jimmy Chandra Jonathan Jonathan Josua Yoprisyanto Julyan Adi Saputra Julyan Adi Saputra Julyanto Julyanto Junifer, Junifer Juzariah Juzariah Juzariah, Juzariah Kelvin Wijaya, Kelvin Kelvyn Kelvyn Kelvyn Kendrik Jonatan Kenny Wilson Lubis, Nywara Natriyasmara Melsen Melsen Muhamad Dody Firmansyah Muhammad Ardiansyah Muhammad Dody Firmansyah Mungkap Mangapul Siahaan Novita Putri Parlindungan Tampubolon Petrick Handy Putra Prasetyo, Stefanus Eko Purwandi, Nellsen Puspitasari, Divanaka Putra, Muhamad Zhabiyan Dwi Putri, Novita Randa Liling, Jenary Regina, Alya Renata, Doreen Rio Fernando, Rio Rosario, Rakit Ricardo Ryan Gunawan Ryo Winata Salsabila, Nanda Salsabilah, Anisah Sama, Hendi Setiawan, Aldovanda Haflah Shanata Limanto Sherlyn, Sherlyn Shermay Sihombing, Angelika Putri Stephanie Stephanie Steven Steven Susanti, Aida Suwarno Suwarno Liang Suwarno Suwarno Suwarno Suwarno Tjahyadi, Surya Tony Jack Tan Ding Welliam Ali Welliam Ali Wilson Wilson Wiyandi, Wiyandi Yang, Jason Aaron Yasa, Irma Sefina Yoprisyanto, Josua Yu Lun Zoin, Shania Zulkarnain Zulkarnain Zulkarnain, Nur Zareen