The Comparison between Bayes and Certainty Factor Method of Expert System in Early Diagnosis of Dengue Infection | Zendy

Eka Yuni Rachmawati | Zendy; Budi Prasetiyo | Zendy; Riza Arifudin | Zendy

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The Comparison between Bayes and Certainty Factor Method of Expert System in Early Diagnosis of Dengue Infection

Author(s) -

Eka Yuni Rachmawati,

Budi Prasetiyo,

Riza Arifudin

Publication year - 2018

Publication title -

scientific journal of informatics

Language(s) - English

Resource type - Journals

eISSN - 2460-0040

pISSN - 2407-7658

DOI - 10.15294/sji.v5i2.15740

Subject(s) - dengue fever , bayes' theorem , certainty , naive bayes classifier , medical record , computer science , artificial intelligence , medicine , statistics , machine learning , bayesian probability , mathematics , virology , geometry , support vector machine

The development of existing artificial intelligence technology has been widely applied in detecting diseases using expert systems. Dengue Infection is one of the diseases that is commonly suffered by the community and may cause in death. In this study, an expert diagnosis system for dengue infection is made by comparing between both Bayes method and Certainty Factor. The aims are to build an expert system using Bayes and Certainty Factor for early diagnosis of dengue infection and also to determine their level of accuracy. There are 80 data used in this study which are obtained from the medical records of Sekaran Health Center in Semarang City. The test results show that the level of accuracy obtained from 80 medical record data for Bayes method is 90% and the Certainty Factor method is 93,75%.

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