Deteksi Masker dan Suhu Tubuh untuk Kendali Portal Otomatis Menggunakan CNN sebagai Pencegahan Penularan SARS-CoV-2 - Ichsan Ali Rachimi; Fitri Utaminingrum (Fakultas Ilmu Komputer (FILKOM), Universitas Brawijaya, 2021)
COVID-19 can be spread through droplets from the nose or mouth that come from a patient infected with COVID-19. If people breathe in the splash with a person who is infected with this virus, they may be infected with COVID-19. Therefore, it is very important for us to maintain a minimum distance of 1 meter and always use a mask to prevent the spread of coronavirus. These splashes can stick to other objects and surfaces, such as tables, door handles and handrails. Because of the importance of using masks during the Covid-19 pandemic, this study will apply the Convolutional Neural Network method to detect mask users, so that in its implementation the system can detect when someone is not wearing a mask and has a body temperature above the normal number, which is above 37.5 Â° C. then the system will automatically close the latch, this is intended so that people always use masks during the COVID-19 pandemic and care about the spread of the virus. The average error value is 1,48% on the infrared sensor and the accuracy at the integration testing stage of the mask detector and infrared temperature sensor MLX90614 at the 9G micro servo output gets an accuracy of 100%.