Software Development to Detecting the use of Mask using Convolutional Neural Networks

Abstract

This research aims to develop software that can detect faces that use masks, do not use masks, and use masks in incorrect positions with the TensorFlow library applying the Convolutional Neural Network (CNN) method. The software development method used is the Incremental Method. Incremental one focuses on building a CNN model using the evaluation of the confusion matrix and incremental two focuses on developing a software display using black box testing. The result in incremental one is a CNN model with a confusion matrix evaluation resulting in a model that has 98.83% accuracy, 98.84% precision, 98.78% recall, and 98.81% fl-score. The second incremental result is the display of the software that has been black box tested and is ready to be used for detection. The final result of this research is software that can detect human face objects using masks, not using masks, and using masks in the incorrect position