Expert System for Early Detection of Public Anxiety Levels Against Covid-19 with the Comparison Method of Dempster-Shafer and Certainty Factor - Adi Firman Ari Saputra; Agung Triayudi; Endah Tri Esti Handayani (Institute of Computer Science (IOCS), 2020)
Anxiety can attack anyone, including society, against Covid-19. Excess anxiety can cause people to experience psychosomatic problems. Based on the existing problems, a system is needed that can help provide information to detect people's anxiety levels and deal with excessive anxiety levels quickly. The method used in this research is the Dempster-Shafer and Certainty Factor methods, which will then be compared to determine the accuracy value of each method. The method that has the highest accuracy value will be applied in the expert system to be created. From the calculation accuracy obtained on the certainty factor method, the accuracy results are 91% and the dhemster-shafer method the accuracy results are 54.5%. Then it can be concluded that the certainty factory method has a more accurate accuracy than the dhamster-shafer method in detecting early levels of anxiety society against covid-19. The research carried out aims to analyze the results of the comparison of the diagnosis of an expert system made in early detection of the level of anxiety in the community about Covid-19.