Implementation of Automatic Attendance System Based on Face Recognition Using CNN Method in IPB University Vocational School Environment

Dini Nurul Azizah; Raisa Mutia Thahir; Luthfi Dika Chandra; Muhammad Naufal Ardhani; Endang Purnama Giri; Gema Parasti Mindara

doi:10.61132/ijmeal.v1i4.94

Authors

Dini Nurul Azizah IPB University
Raisa Mutia Thahir IPB University
Luthfi Dika Chandra IPB University
Muhammad Naufal Ardhani IPB University
Endang Purnama Giri IPB University
Gema Parasti Mindara IPB University

DOI:

https://doi.org/10.61132/ijmeal.v1i4.94

Keywords:

Automatic Attendance System, Face Recognition, CNN, Python, OpenCV

Abstract

The research focuses on creating an automated attendance system using face recognition through the Convolutional Neural Network (CNN) approach at IPB University's Vocational School. The current manual attendance methods show limitations, such as potential inaccuracies in recording and the risk of cheating, like attendance proxies. To overcome these challenges, this study applies the CNN approach with Python and OpenCV, enabling automatic face detection and recognition for students. The system accurately logs attendance by identifying faces in real time. Testing indicates that the system records attendance reliably, whether with a single individual or with multiple faces present within a single frame.

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