PERBANDINGAN CITRA RGB DAN GRAYSCALE UNTUK KLASIFIKASI WAJAH BERMASKER MENGGUNAKAN METODE CONVOLUTIONAL NEURAL NETWORK

Muhammad Sabirin (Universitas Mataram)

Jurnal Teknologi Informasi, Komputer, dan Aplikasinya (JTIKA )
Vol 5 No 2 (2023): September 2023

significance of mask usage, many individuals have not been using them correctly. In order to address this issue, a system for image processing was developed using Convolutional Neural Network (CNN) capable of identifying three categories: wearing masks correctly, wearing masks incorrectly, and not wearing a mask. The dataset employed consists of 500 images for each category. Additionally, a comparison between using RGB and grayscale images was conducted, revealing that the RGB-based image model achieved an accuracy of 94.78%, while the Grayscale image reached an accuracy of 89.22%. These results confirm the importance of color information in the mask-wearing position detection process. Through this research, it is hoped to contribute to raising public awareness regarding the significance of proper mask usage in the efforts against Covid-19.