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All Journal International Journal of Research and Applied Technology (INJURATECH)
Ardhi Fadli Firdaus
Departemen Teknik Elektro, Universitas Komputer Indonesia, Indonesia
Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Mask Detection Using Image Processing Alvin Gusti Prabowo; Ardhi Fadli Firdaus; Gian Syahdatal Rizal
International Journal of Research and Applied Technology (INJURATECH) Vol 3 No 1 (2023): International Journal of Research and Applied Technology (INJURATECH)
Publisher : Universitas Komputer Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34010/injuratech.v3i1.10013

Abstract

In early 2020, the epidemic of a new type of pneumonia led by Wuhan, Hubei shocked the world, and then spread rapidly to more than 190 countries and regions. This outbreak is named Coronavirus Disease 2019 (COVID-19) caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). The spread of this disease has widespread social and economic impacts. Therefore, during the current COVID-19 pandemic, regulations are enacted in which everyone is required to wear a mask and perform physical distancing when leaving the house in Indonesia to reduce the spread of COVID-19. The purpose of this study is to be able to create a detect the use of masks using deep learning methods with Alex net network type. The results showed that the development masks can be applied at the entrance of a mall or hospital by installing a detection device in front of the entrance. It can also be seen the results of the detection on a computer that has been integrated with the detection system. This research is useful to make it easier for people to wear masks or not and detect it automatically without having to do it manually by officers.
Co-Authors Alvin Gusti Prabowo Gian Syahdatal Rizal