SISTEM DETEKSI PEMAKAIAN MASKER PADA WAJAH SECARA REAL TIME MENGGUNAKAN FRAMEWORK TENSORFLOW DAN LIBRARY OPENCV - Althaf Adhari Rachman; Ivan Maurits (Jurnal Ilmiah Teknik, 2023)
At the end of December 2019, there was a mysterious virus that attacked the city of Wuhan in China. Which at the beginning of 2020 the new virus was a new type, namely (SARS-CoV-2) and the disease was called Coronavirus disease 19 (COVID-19). The World Health Organization (WHO) provides instructions to maintain a minimum distance of 1 meter, always wash hands with soap, and always use a mask when leaving the house. The purpose of this writing is to create a program to detect wearing masks on the face, which makes it easier for users to detect who is wearing a mask or not. The method used in this writing uses the SDLC model or System Data Life Cycle by carrying out five stages namely, planning, analysis, design, implementation, and testing. The design uses flowcharts and navigation structures as well as two UML diagrams, namely use case diagrams and activity diagrams. Then for making the program using Python as a programming language, Tensorflow as a framework, Keras and Opencv as libraries, and Visual Studio Code as a text editor. From the results of trials that have been carried out using three different devices and with different specifications, this system can detect mask objects very well and this detection system can also detect more than one person wearing a mask, or not wearing a mask.