Klasifikasi Besar Potensi Kemunculan Batu Ginjal Menggunakan Fuzzy Inference System (FIS) Metode Mamdani

Abstract

The phenomenon of modernization that arises in the lives of society has an impact on unhealthy lifestyles. This has led to an increased prevalence of kidney stone disease in recent decades. In this study, a fuzzy inference system will be developed using the Mamdani method for the classification of the large potential occurrence of kidney stones based on urine conditions. The input variables used are urine pH, urea content in urine, and calcium content in urine, while the output variable used is the magnitude of the potential occurrence of kidney stones. The variables included in the fuzzy set are formed by combinations of each variable with its respective linguistic terms. These fuzzy sets are then processed with the help of Matlab software to produce a classification result indicating small or large potential. The classification results from the developed fuzzy inference system provide accurate classifications for users with an accuracy level of 94%. Thus, in general, this fuzzy system can be used to assist in classifying the large potential occurrence of kidney stones, thereby minimizing the number of individuals suffering from this disease as much as possible.