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All Journal Jurnal Indonesia : Manajemen Informatika dan Komunikasi
Virgiawan Restu Pratama
Universitas Sains dan Teknologi Komputer
Computer Science & IT Languange, Linguistic, Communication & Media Library & Information Science

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Perancangan Sistem Deteksi Wajah Real-Time Menggunakan Convolutional Neural Network pada Perangkat Komputer Desktop Virgiawan Restu Pratama; Dani Sasmoko; Toni Wijanarko Adi Putra
Jurnal Indonesia : Manajemen Informatika dan Komunikasi Vol. 7 No. 3 (2026): September
Publisher : Lembaga Penelitian dan Pengabdian Kepada Masyarakat (LPPM) STMIK Indonesia Banda Aceh

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63447/jimik.v7i3.1982

Abstract

This research aims to design and implement a real-time face detection system use a Convolutional Neural Network (CNN) on a desktop computer. The research consisted of data preprocesing, collection, model training, and performance evaluation. The dataset contained 200 facial images, which were resized to 224 ×is 224 pixels, normalized, and divided into training and testing sets. The model was developed using TensorFlow, Keras, and OpenCV, and evaluated use confusion matrix based on precision, accuracy, recall, and F1-score. The research results is that the proposed model can detect and recognize faces effectively, as demonstrated by an accuracy value of 97.22%, along with recall, precision, and F1-score values of 97%. The implementation of Batch Normalization and Dropout improved training stability and enhanced the model's generalization capability. These findings indicate that the CNN -based approach is effective for real-time face detection on desktop computer systems.
Co-Authors Dani Sasmoko Toni Wijanarko Adi Putra