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All Journal Journal of Intelligent Decision Support System (IDSS)
Siti Ilya Suwella
STMIK Pelita Nusantara
Computer Science & IT

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Expert System Diagnosing Diabetes Using the Web-Based Dempster Shafer Method Siti Ilya Suwella; Fristi Riandari
Journal of Intelligent Decision Support System (IDSS) Vol 4 No 4 (2021): December: Intelligent Decision Support System (IDSS)
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/idss.v4i4.31

Abstract

Diabetes is a very dangerous disease because diabetes can attack other organs of the body so that it can cause death. This is due to the lack of technology-based information that can help determine the symptoms of diabetes. With the limited number of diabetes experts, an expert system is needed to diagnose diabetes. The method applied to the system is the Dempster Shafer method, by determining 17 symptoms and 3 types of disease, as well as compiling a rule base in determining the relationship of each symptom so that the results in the calculation achieve 100% accurate results. This method has 5 steps in its completion. The results showed that the Dempster Shafer method could be used to diagnose the symptoms of diabetes. So that the existence of this system can help the wider community in finding information about the symptoms of diabetes.
Co-Authors Fristi Riandari