Diagnosis Of the Diabetes Mellitus disease with Fuzzy Inference System Mamdani

Za’imatun Niswati, Aulia Paramita, Fanisya Alva Mustika

Abstract

Patients diabetes mellitus increased from year to year. This is due to delays in diagnosis of the disease and also because of unhealthy lifestyles. This study aims to create an application of decision support systems in the field of health, namely the diagnosis of the Diabetes Mellitus disease with Fuzzy Inference System (FIS) Mamdani, so that a layman can perform early diagnosis and immediate treatment. Decision Support System Techniques developed to improve the effectiveness of decision-makers. Samples are six Puskesmas in East Jakarta. This application uses five variables as inputs consisting of glucose 2 hours after a meal, Diastolic blood pressure, body mass index, family history of diabetes. the number of pregnancies and one variable as output. The data obtained will be processed using fuzzy logic approach to programming matlab and made Graphical User Interface (GUI). The  result is an expert system for diagnosis of Diabetes Mellitus by using Fuzzy Inference System (FIS) Mamdani method, obtained an accuracy rate of 95%. It is  to help improve the quality of service in the Puskesmas in East Jakarta, thus satisfying the users and Puskesmas be able to compete both nationally and internationally.

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