Identifikasi ciri penyakit COVID-19 menggunakan metode Wavelet Deubechies-2

Irtawaty, Andi Sri; Ulfah, Maria; Nurwahidah, Nurwahidah; id,

Coronavirus is a type of virus that can cause mild to severe illness. Transmission from animals to humans (zoonosis) and transmission from humans to humans is very limited. The main symptoms of COVID-19 are six, namely chills, chills, muscle aches, headaches, sore throats, and loss of sense of smell accompanied by a greater body temperature of 380C, Other symptoms such as skin rashes, dizziness and redness of the eyes. The incubation period is 2-14 days. This disease has become a pandemic, the number 1 cause of death in the world today. In this research, a process of identifying the characteristics of COVID-19 will be carried out based on the appearance of lung X-ray images. There are 9 samples of lung X-ray images that will be identified by their characteristics. The image processing method used is the Wavelet Deubechies 2 (Wavelet DB2) method. The processing technique is by displaying images in binary format and displaying the values ​​of approximation energy, horizontal energy, vertical energy, diagonal energy and the detailed energy of each lung image. Of the 9 sample images tested there were 4 samples of healthy lung images and 5 samples of lung images infected with the COVID-virus 19. It turned out that the energy value of healthy lung images was greater than the energy value of COVID-lung images 19. The accuracy of the method DB2 wavelet in identifying the characteristics of COVID-lung images 19 about 78%.