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Dinda Ramadhani
Universitas Sumatera Utara
Computer Science & IT Decision Sciences, Operations Research & Management

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Web-Based Expert System for Diagnosis Mycetoma Using Dempster-Shafer Methods Dewi Sartika Br Ginting; Dinda Ramadhani
Bahasa Indonesia Vol 15 No 01 (2023): Instal : Jurnal Komputer
Publisher : Cattleya Darmaya Fortuna

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.54209/jurnalkomputer.v15i01.52

Abstract

Health is very important and valuable for humans, because without good health, every human being will experience difficulties in carrying out their daily activities. Mycetoma disease, also known as fungal infection and flesh-eating disease, affects people who live in rural or remote areas and have limited access to health care and medicines. So to overcome this problem, we need an expert system that is able to diagnose mycetoma based on the symptoms suffered. The expert system for diagnosing mycetoma using the Dempster Shafer method is designed as a tool for early identification of mycetoma. The Dempster Shafer method was chosen because data collection (weight) for the Dempster Shafer calculation is relatively easy to do just by giving an expert's trust value for a symptom. The calculation process for obtaining conclusions is also relatively easy to do because in the calculations the Dempster-Shafer theory only involves the probabilities of all possible diseases from each symptom.
Co-Authors Dewi Sartika Br Ginting