SISTEM PAKAR UNTUK MENDUKUNG POLA MAKAN PENDERITA DIABETES MELITUS TIPE 2

Abstract

In Indonesia, the number of people with Type 2 Diabetes Mellitus continues to increase, often experiencing difficulties in managing their diet due to limited time and access to nutritionists. This worsens health and increases the risk of serious complications such as kidney failure and heart disease. To solve this problem, a web-based expert sistem using the Certainty Factor (CF) method was developed. This method is effective in handling uncertainty in medical diagnosis. By collecting the user's health data, such as height, weight, physical activity, blood sugar level, and stress level, the sistem calculates the certainty to provide personalized dietary recommendations.

This research went through several stages, namely Problem Formulation, Sistem Design, Implementation, Evaluation, and Feedback Collection. Problem formulation is done by identifying the challenges and needs faced by people with type 2 diabetes mellitus in choosing a healthy diet. The next stage is sistem development that starts with the design stage, where an initial prototype is created. The next stage is the implementation of the sistem in a real environment. At this stage, data is collected from users who use the sistem to get the right dietary recommendations. In the next stage, feedback from users is collected to identify weaknesses and areas that need improvement.

Results indicate that the CF method effectively provides accurate and accessible dietary recommendations, helping maintain stable blood sugar levels and reduce complication risks. Despite the lack of formal testing, the sistem shows significant potential to enhance the quality of life for diabetes patients.