ABSTRACT
Since the outbreak of the COVID-19 virus, various technologies have developed as an alternative to preventing the spread of the COVID-19 virus;one of them is face mask detection. Many methods are used, such as Convolutional Neural Network, Haar cascade classifier, and more. This paper discusses how the system will work with face mask detection and the performance result while running the system against the parameters that can occur during training or direct testing by comparing several different methods. The test results display in the form of a line graph, and the Haar Cascade Classifier method will be displayed in tabular form, with the highest accuracy in the CNN method being 93%, while the Haar Cascade Classifier method is 96% © 2022 Institute of Advanced Engineering and Science (IAES).
ABSTRACT
In this paper, it is a solution to assist government policies in reducing the spread of the 2019 coronavirus disease (COVID-19) at Mercu Buana University, where the system is designed to function as an online admissions interface using fuzzy logic with artificial intelligence. Where the system is fully automatic, starting from processing input data and output data in the form of selection results made by the system in real-time. Fuzzy logic for the lower limit value which is considered very low is 50 and the upper limit is 55. For the low category value, the lower limit is 50 and the upper limit is 65. For medium category values the lower limit is 63 and the upper limit is 78. And for high category values, the limit is lower than 77, and an upper limit of 85. © 2021 IEEE.