Object Detection for Using Mask in COVID-19 Pandemic with Faster R_CNN Inception V2 Algorithm

When this research was done, based on data from https://​covid19.​go.​id/​, the number of positive patients reached 127,083, the increasing number of COVID-19 patients in Indonesia, and the new normal period had been imposed, making people more concerned about the health and the danger of spreading COVID-19 virus. New normal means were starting a new habit that is the habit of washing your hands and use a mask. Everyday activities in normal times require us to work as usual, in an atmosphere with other people. Everyone is required to use a mask to support the policy of using a mask, a system that can detect whether someone is wearing a mask or not. This research aims to be able to identify the use of masks in public areas. The dataset used is 5000 images of people wearing masks. This research uses the Faster R_CNN Inception V2 Algorithm. And then the results were evaluated using COCO mAP Score yielding in 0.58 mAP, with 0.78 mAP for large objects, 0.65 mAP for medium objects, and 0.48 mAP shows this research can contribute to the community to care in the use of masks. The model that has created in this study is used to detect the use of masks in public areas by using an image captured by a camera mounted in a particular place.