Diagnosing MERS-CoV using dempster-shafer method - Memen Akbar; Fandy Hidayat; Wenda Novayani (Institute of Advanced Engineering and Science, 2021)
MERS-CoV (Middle East Respiratory Syndrome-Coronavirus) is a respiratory syndrome disease caused by the coronavirus which attacks the respiratory tract from mild to severe. MERS-CoV was first reported in Saudi Arabia; total cases of MERS-CoV have continued to increase. In Indonesia, the MERS-CoV enters through the pilgrimage of Hajj and Umrah. But not many people know about this disease and its symptoms. For this reason, an expert system was developed to diagnose MERS-CoV using the Dempster-Shafer method. The system can detect the disease from the symptoms inputted by user. The output of the system is the value of the probability of the disease, the level of the disease and the suggested. The levels of the disease are Stage 1, Stage 2, and Stage 3 where each has a different treatment based on the level of the disease. The system contains information about MERS-CoV in the form of videos and text. The system was built using the PHP programming language. The testing result shows that all system functionalities have been fulfilled. The expert validation testing had obtained at 76.7%, which prove that the system is good enough in diagnosing MERS-CoV and the results obtained from the questionnaire is at an average of 84.13% which is very good in helping users in diagnosing disease. The expert system that has been developed can help people in diagnosing the disease before consulting with a doctor.MERS-CoV (Middle East Respiratory Syndrome-Coronavirus) is arespiratory syndrome disease caused by the coronavirus which attacks therespiratory tract from mild to severe. MERS-CoV was first reported in SaudiArabia; total cases of MERS-CoV have continued to increase. In Indonesia,the MERS-CoV enters through the pilgrimage of Hajj and Umrah. But notmany people know about this disease and its symptoms. For this reason, anexpert system was developed to diagnose MERS-CoV using the DempsterShafer method. The system can detect the disease from the symptomsinputted by user. The output of the system is the value of the probability ofthe disease, the level of the disease and the suggested. The levels of thedisease are Stage 1, Stage 2, and Stage 3 where each has a different treatmentbased on the level of the disease. The system contains information aboutMERS-CoV in the form of videos and text. The system was built using thePHP programming language. The testing result shows that all systemfunctionalities have been fulfilled. The expert validation testing had obtainedat 76.7%, which prove that the system is good enough in diagnosing MERSCoV and the results obtained from the questionnaire is at an average of84.13% which is very good in helping users in diagnosing disease. Theexpert system that has been developed can help people in diagnosing thedisease before consulting with a doctor.