E-Pindai: Pengolahan Citra Wajah Pendeteksi Penggunaan Masker dengan Metode Convolution Neural Network

Abstract

Virus yang menyebabkan Covid-19 disebut SARS-CoV-2 menyebar secara cepat bila ada kontak erat dalam jarak sekitar 2 meter. Penggunaan masker merupakan salah satu cara menghindari penularan penyakit ini. Dalam penelitian ini dikembangkan alat pendeteksi penggunaan masker yang selanjutnya disebut E-Pindai. E-Pindai merupakan inovasi berbasis teknologi pengolahan citra menggunakan metoda Convolution Neural Network (CNN) dan Internet of Things (IoT). Sistem ini dipasang di Abstract The virus that causes Covid-19, called SARS-CoV-2, spreads quickly when there is close contact within about 2 meters. Wearing a mask is one way to prevent the spread of this disease. In this study, a mask detection tool was developed, hereinafter referred to as E-Scan. E-Scan is an innovation based on image processing technology using the Convolution Neural Network (CNN) and Internet of Things (IoT) methods. This system is installed at the entrance gate of a public area where every visitor who enters his face will be scanned. If it is detected that you are not wearing a mask, the door remains closed, the buzzer sounds, and a photo of the face is sent to the Covid-19 Task Force via the Telegram application as a notification. If all visitors wear masks, the door will open automatically. Data processing is carried out using a Raspberry Pi that has been filled with the program using the Python programming language. The processed data will produce a logic number 1 or 0 which becomes the command code to move the servo motor to open or close the gate, and activate or deactivate the buzzer. The results of testing on 17 types of masks using the confusion matrix method resulted in a percentage of 94% accuracy, 100% precision, 94.11% sensitivity, 100% specificity, and 5.56% error rate. Analysis of image capture distance and response time was also carried out to see the response of the device made.