An Application For Detection Of Confidential Disease For The Prevention Of Covid 19 Based On Mobile

Abstract

Coronavirus disease (Covid19) is an infectious disease caused by the SARSCoV2 virus. Most people infected with COVID-19 show mild to moderate symptoms and recover without specific treatment. However, around 4,444 people are seriously ill and need to see a doctor. The purpose of using information technology to create a comorbid population identification system is to create a classification model for residents with congenital diseases for the prevention of Covid19. This study aims to identify people who have comorbidities using information technology according to evidence of congenital disease. The system development method used is the waterfall method. This survey flow describes the stages or survey procedures of the Covid19 classification application which aims to facilitate the classification of residents with congenital diseases. The result find is an application system or website for the classification of disease detection using a mobile website. This website can classify or classify diseases based on the characteristics and criteria of the disease. When conducting tests, this website facilitates and assists in accessing disease data, especially congenital and chronic diseases. According to the results of this website, it is easy for them to see the name of the disease and the symptoms they are suffering from as a form of preventing the transmission of Covid-19.