Sistem Deteksi Masker Dan Pengenalan Wajah Menggunakan Algoritma Convolutional Neural Network

Sari

During the current COVID-19 pandemic, the use of masks is mandatory for everyone when carrying out various activities to prevent the spread of the COVID-19 virus. So far, the detection of the use of masks has been done manually through observation by officers. This method has several limitations, namely it cannot be done every time and every place. Based on these problems, the researchers designed a Mask Detection System and Face Recognition Using Convolutional Neural Network. This system is designed for the Department of Information and Computer Technology at the Lhokseumawe State Polytechnic. The system input is in the form of a real-time video camera that can detect students both wearing masks or not and every student who does not use a mask will be recognized by his face. The system will send a notification to the officer if there are students who do not wear masks. The system uses a mask dataset taken from the data on the Kaggle website and for facial recognition the system uses facial data from 4C IT class students. The results obtained in the making of the CNN model that were tested resulted in 99% accuracy and realtime testing resulted in an overall accuracy rate of 75%, mask detection accuracy of 83%, face detection accuracy of 71%. Keywords — Convolutional Neural Network, Mask Detection, Notification, Face Recognition