TY - JOUR AU - Radimas Labib AU - Sirojul Hadi AU - Parama Widayaka PY - 2021/11/26 Y2 - 2024/03/29 TI - Low Cost System for Face Mask Detection Based Haar Cascade Classifier Method JF - MATRIK : Jurnal Manajemen, Teknik Informatika dan Rekayasa Komputer JA - matrik VL - 21 IS - 1 SE - Articles DO - https://doi.org/10.30812/matrik.v21i1.1187 UR - https://journal.universitasbumigora.ac.id/index.php/matrik/article/view/1187 AB - In December 2019, there was a pandemic caused by a new type of coronavirus, namely SARS-CoV-2 (Severe Acute Respiratory Syndrome Corona Virus 2) spread almost throughout the world. The World Health Organization (WHO) named it COVID-19 (Coronavirus Disease). To minimize the spread of the COVID-19, the Indonesian government announced a policy for the social distancing of 1-2 meters and wearing a medical mask. In this study, a mask detection system was built using the Haar Cascade Classifier method by detecting the facial areas such as the nose and lips. The study aims to distinguish between using masks and on the contrary. It is expected that the mask detection system can be implemented to provide direct warnings to people who do not wear masks in public areas. The results using the Haar Cascade Classifier method show that the system designed is able to detect faces, noses, and lips at a light intensity of 80-140 lux. The face is detected at a distance of 30-120cm, while the nose is at a distance of 30-60cm, while the lips are at a distance of 30-70cm. The system designed can perform the detection process at a speed of 5 fps. The overall test results obtained a success rate of 88,89%. ER -