PENEREAPAN FUZZY LOGIC DALAM ANALISIS RESIKO PASIEN DIABETES DAN HIPERTENSI

Abstract

Diabetes and hypertension are two chronic conditions that often occur simultaneously and exacerbate each other, worsening the patient’s overall health. Risk analysis of these two diseases requires an approach capable of handling uncertain and complex medical data. In this study, the fuzzy logic method is applied to analyze the risk of patients suffering from diabetes and hypertension. Fuzzy logic allows for more flexible assessment of clinical data such as blood glucose levels, blood pressure, body mass index, and history of complications by transforming numerical data into linguistic values that are easier to interpret. The developed fuzzy model uses several input variables to determine the patient's risk level, which is categorized into low, medium, and high risk. The analysis results indicate that the fuzzy approach is more adaptive to patient data variations compared to conventional methods, and it provides risk assessments that are more realistic and easier for medical personnel to interpret. Therefore, the implementation of fuzzy logic in medical decision support systems can improve the accuracy of early diagnosis, assist in clinical decision-making, and support more precise intervention planning for patients with diabetes and hypertension