Design and Development of Mask Detectors in Effort to Prevent the Spread of Hepatitis Post-Covid-19 Pandemic using Viola-Jones Algorithm

Author

Assoc. Prof. Dr. Agus Nursikuwagus, ST.,MT.,MM.

Abstrak

In the current New Normal Era, people are starting to be free to do activities outside the house, with the condition of wearing a mask to prevent the coronavirus. After the number of cases of the Covid-19 pandemic began to decline, the World Health Organization (WHO) received a report on April 5, 2022, from the United Kingdom regarding cases of acute hepatitis that began to spread in children and whose aetiology was unknown. The spread of the disease can be through the air, so everyone must wear a mask outside the house. Through the Ministry of Health, the Indonesian government reported that as of June 16, 2022, at 16.00, there were 28 suspected cases of severe acute hepatitis with unknown or mysterious causes for Indonesian children. This number increased by three cases from the June 9, 2022 report. Of the 28 cases, there were 13 probable and 15 pending classifications in classifying hepatitis. This research aims to design a mask detector that assists in monitoring health protocols by detecting the use of masks in public areas or office buildings so that they can continue to carry out everyday activities during the pandemic. The design of this mask detection tool uses the Viola-Jones Algorithm, where this method has four primary keys, namely the Haar feature, Integral Image, adaboost, and cascade classifier. Based on the test results, this mask detector can detect mask objects at a distance of 1 to 2 meters, with a limit of the number of people detected up to 3. Future research is expected to be able to develop a mask detection device using raspberry pi hardware to replace the arduino uno to better suit system needs and also add a sound system.