Pengembangan Sistem Pakar Diagnosis Penyakit Ginjal Kronik Menggunakan Metode FIS - Sugeno

Jumadi Jepri


The number of patients with Chronic Kidney every year always increases. One of the causes is the late diagnosis to be known and the existence of an unfavorable lifestyle. The United Nations Alliance (WHO) estimates that in Indonesia there will be an increase in kidney failure patients until 2025 by 41.4%. In this study an expert system for diagnosing Chronic Kidney disease will be made using the FIS - Sugeno method. The variables used in the formation of fuzzy sets which are variable sets of laboratory results include creatinine, urea, hemoglobin, blood pH, urine albumin, and gout. Variables that have been entered in the fuzzy set are formed by a combination of one variable with the linguistics of each then the fuzzy set will be processed by the FIS-Sugeno method with the help of the Matlab Toolbox so as to produce a decision in the form of chronic kidney negatives, chronic pre kidney or chronic kidney positives. This application was tested by involving medical records of diagnoses from doctors using variables: creatinine, urea, hemoglobin, blood pH, albumin and acidic letters. The results of the decisions generated from the application using the Sugis-FIS method resulted in accurate decisions for users in diagnosing chronic kidney disease. Thus in general this application can be used to assist in the diagnosis of chronic kidney disease so that the spread of the disease can be suppressed as much as possible.


Expert System; Fuzzy Inference System; Sugeno Method; Toolbox Matlab

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