Diagnosing MERS-CoV Using Dempster-Shafer Method
Penulis: Akbar, Memen
Abstrak 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 established to diagnose MERS-CoV using the Dempster-Shafer method. The system can detect the disease through the symptoms inputted by the user. The output of the system is the value of the probability of the disease, the level of the disease and the solution. The levels of the disease are Stage 1, Stage 2, and Stage 3 where each has a different solution based on the level of the disease. In the system, there is information about MERS-CoV in the form of videos and text. The system has been built using the PHP programming language. After testing, the results show that all system functionality has been fulfilled. The expert validation testing had obtained at 76.7%, which is good in diagnosing MERS-CoV and the results of the questionnaire obtained at average of 84.13% which is very good in helping users in diagnosing disease. The expert system that has been built can help people in diagnosing the disease before consulting a doctor.
Jurnal: International Journal of Informatics and Communication Technology (IJ-ICT) Vol 10, No 1: April 2021
Published: Institute of Advanced Engineering and Science
IJICT http://ijict.iaescore.com/index.php/IJICT ISSN : 22528776, EISSN : 27222616, DOI : -,
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Location: Kota yogyakarta, Daerah istimewa yogyakarta INDONESIA
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