Expert System for Initial Diagnosis of Covid-19 Using the Forward Chaining Method and Ripple Down Rules

In late 2019, a new infection was identified in Wuhan, China. This disease has been designated by WHO as Corona Virus Disease (Covid-19). The Covid-19 has been spreading rapidly to Indonesia. Several types of variants, such as alpha, delta and Omicron, have been identified by WHO. An expert system that can recognise Covid-19 at an early stage should be developed to limit its spread as a result of the number of cases of patients and variants. In order to cope with future changes in knowledge, the author developed the “SiskaCov” expert system for early detection of Covid-19 based on the symptoms of each variant using the forward chaining method and the ripple down rule as a method of knowledge acquisition. The expert system is built with the Expert System Development Life Cycle (ESDLC). The evaluation process is based on a series of steps but only the stages of knowledge acquisition, design and testing are carried out. Siska-Cov was built based on WEB using PHP Native and Javascript. This system was tested on 62 respondents, the test results shows that the performance value, the ease of use, and the usability value of the system are correlate with user behaviour regarding further use of this expert system.