Implementation of Expert System for Diabetes Diseases using Naïve Bayes and Certainty Factor Methods


Muhammad Ilham Insani1, ,, - and Alamsyah, FMIPA Ilkom and Anggyi Trisnawan Putra, - (2018) Implementation of Expert System for Diabetes Diseases using Naïve Bayes and Certainty Factor Methods. Scientific Journal of Informatics, 5 (2). pp. 185-193. ISSN 2407-7658

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Abstract

Expert Systems is a computer systems that has been entered the base knowledge and a set of rules used to solve problems like an expert. Methods that can be used in the expert systems which is Naïve Bayes and Certainty Factor. Naïve Bayes method can handle quantitative calculations and discreate data and only requires a little research data to estimate the parameters needed in the clasification and Certainty Factor which is suitable for measuring something whether it is certain or not in diagnosing. Diabetes is one of the most frequent diseases suffered in Indonesia. The purpose of this research is implementation expert systems used Naïve Bayes and Certainty Factor in diagnosing diabetes and knowing the level of accuracyof the systems. Data that is used by researchers as much 100 data medical record, obtained from the medical record RSUD Bendan Kota Pekalongan. The variabels used in this research is age, gender, the symptoms of the desease diabetes and result diagnose desease from expert. The accuracy rate of this system derived from the scenario distribution data 70 training data and 30 testing data that is equal to 100% according to the doctor's diagnosis.

Item Type: Article
Uncontrolled Keywords: Expert Systems, Disease Diabetes, Naïve Bayes, Certainty Factor
Subjects: T Technology > Information and Computer
Fakultas: Fakultas Matematika dan Ilmu Pengetahuan Alam > Ilmu Komputer, S1
Depositing User: mahargjo hapsoro adi
Date Deposited: 11 Jun 2021 07:13
Last Modified: 11 Jun 2021 07:13
URI: http://lib.unnes.ac.id/id/eprint/44094

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