Klasifikasi Penggunaan Masker Wajah Menggunakan Squeezenet - Parmonangan R. Togatorop; Ahmad Fauzi (Lembaga Penelitian dan Pengabdian pada Masyarakat (LPPM) STMIK Global Informatika MDP, 2022)
The Covid-19 pandemic caused by Sars-Cov2 virus has caused the damage of the human respiratory system. Therefore, the government give a recommendation to all of us for using a personal protective equipment like a face mask when everyone is doing an activity in the outdoor to prevent the spread of the Sars-Cov2. The purpose of this study is to build a classification model to be able to determine whether someone uses a mask or not. The building model used in this study is SqueezeNet for feature extraction and Naïve Bayes, Support Vector Machine for the classification process. Research data to build the model consist of 658 facial images using masks and 656 facial images without masks. The evaluation using 10-Fold Validation is the accuracy of the model using Naïve Bayes is 0.958, precision is 0.981, and recall is 0.938. Using SVM, the evaluation result is for the accuracy is 0.992, precision is 0.994, and recall is 0.990.