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All Journal Jurnal Inovasi Teknologi Terapan
Ayu Fazira, Hanum
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Agriculture, Biological Sciences & Forestry Computer Science & IT Electrical & Electronics Engineering Mechanical Engineering

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Sistem Pengenalan Wajah Mahasiswa Praktikum Di Laboratorium Teknik Elektro dan Informatika Polmanbabel Menggunakan Convolutional Neural Network (CNN) Akbar Nugraha, Fauzan; Ayu Fazira, Hanum; Iqbal Nugraha, Muhammad; Febriansyah, Aan
Jurnal Inovasi Teknologi Terapan Vol. 1 No. 1 (2023): Jurnal Inovasi Teknologi Terapan
Publisher : Politeknik Manufaktur Negeri Bangka Belitung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33504/jitt.v1i1.22

Abstract

Facial recognition is a type of biometric based on human facial features. Face recognition is very important for an institution such as a university where many students make it difficult for employees to recognize students one by one. This study used students as objects and focused on one laboratory room. The goal is to identify anyone who is in the laboratory room. The Convolutional Neural Network (CNN) method with a webcam is used in this study to recognize the faces of students or anyone who enters the laboratory. The system will report anyone caught by the camera including those who are not recognized. Based on the experimental results, data is obtained that the system can recognize objects well up to a distance of 4 maters and the optimum for 100% accuracy is at a distance of 3 meters. Accuracy will decrease if the distance from the object to the camera is less than 3 meters, which is 93,33% for a distance of 2 meters and 86,67% for a distance of 1 meter.
Co-Authors Aan Febriansyah Akbar Nugraha, Fauzan Iqbal Nugraha, Muhammad