Application of Object Mask Detection Using the Convolution Neural Network (CNN)

Application of Object Mask Detection Using the Convolution Neural Network (CNN)

covid-19; object detection; image processing; convolution neural network (CNN); public services

The spread of Coronavirus Disease (Covid-19) is still a serious problem we are currently facing. The spread occurred very
quickly through the process of face-to-face interaction. The process of face-to-face interaction that occurs both in public spaces
and closed spaces has a great risk of transmitting the Covid-19 virus. One of the efforts to deal with the spread of the Covid-
19 virus is by increasing the use of masks both in public and closed spaces. Based on this, this study aims to develop an Object
Detection process in image processing techniques. Object Detection development using the Convolution Neural Network
(CNN) method to provide optimal output. The CNN can process the input image which is converted into a pixel matrix and
then forwarded to the convolution layer. The research dataset consists of 2000 images of face masks and not masks. The images
were obtained from the open sources github.com and kaggle.com. The results of the study present a system capable of detecting
masks in real time. CNN provides very good performance with an accuracy rate of 99.05%. With these results, the contribution
of this research can be used for the process of monitoring public services for the community to increase the use of masks.

Yuhandri, Musli Yanto, Eka Naufaldi Novri

http://jurnal.iaii.or.id

Professional Organization Ikatan Ahli Informatika Indonesia (IAII)/Indonesian Informatics Experts Association

August 2023

Sri Wahyuni

ISSN Media Electronic: 2580-0760

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