Application of Fuzzy Inference System for Quality Assessment of Formula Milk for Pregnant Women in Stunting Program

Abstract

Stunting remains a significant global public health challenge, affecting more than 149 million children under five years of age worldwide as reported by the United Nations in 2020. Indonesia alone accounts for approximately 6.3 million stunted children, highlighting the urgent need for effective intervention strategies. Stunting is primarily caused by chronic malnutrition during the first 1,000 days of life, which includes inadequate nutritional intake during pregnancy, poor infant feeding practices, and environmental factors such as inadequate sanitation. The 2022 Indonesian Nutrition Status Survey (SSGI) indicated a stunting prevalence of 21.6%, showing improvement from 24.4% in 2021, yet still significantly above the national target of 14% set for 2024. Given the critical role of maternal nutrition in reducing stunting risk, providing pregnant women with appropriate nutritional guidance is essential. This study aims to develop a decision support model using a Fuzzy Inference System (FIS) to assist pregnant women in selecting the most suitable formula milk based on nutritional value and affordability. The Mamdani FIS method was applied to analyze data from eight commercially available formula milk products. The evaluation measured the membership degrees corresponding to recommendation levels, factoring in both price and nutrition. The results identified Anmum Materna as the most favorable option, with a membership degree of 0.937, classified under the "Highly Recommended" category. This formula is priced at IDR 70,000 and contains a total nutritional value of 1024 grams, offering a balance of quality and affordability. This model demonstrates potential as a practical tool to support informed nutritional choices during pregnancy, contributing to stunting prevention efforts.