Optimizing the Diet of Diabetes Mellitus Sufferers Through Food Mapping Using the Fuzzy Sugeno Method

Abstract

This research focuses on developing optimal strategies for diet management for Diabetes Mellitus (DM) sufferers by utilizing the Fuzzy Sugeno method in food mapping. Diabetes Mellitus is a chronic metabolic disease that requires a careful management approach to diet to control blood sugar levels. In this study, we designed a system that uses Sugeno's fuzzy principles to categorize foods based on glycemic parameters, nutritional content, and individual patient characteristics. This method allows the formation of fuzzy rules that cover the variability and complexity in the preferences and health needs of each patient. The developed model was tested using DM patient data involving detailed information about diet, medical history and blood sugar response. Experimental results show that this approach can provide more personalized diet recommendations that suit individual health conditions. The application of the Fuzzy Sugeno method in food mapping for DM patients is expected to increase patient compliance with the recommended diet, reduce blood sugar levels, and overall, improve quality of life. Additionally, this approach also provides a foundation for the development of adaptive dietary management systems, which can continuously adapt to changing patient health needs over time.