<![CDATA[Stunting is one of the chronic nutritional problems that remains a major concern in Indonesia, particularly in North Sumatra Province. This condition occurs due to prolonged nutritional deficiencies that affect children’s physical growth and cognitive development. The National Population and Family Planning Agency (BKKBN) of North Sumatra plays an essential role in monitoring and reducing stunting rates. However, the prediction methods currently used are still conventional and have not utilized modern predictive technologies. As a result, the forecasting accuracy is often low because stunting data tends to be fluctuating and influenced by various dynamic factors. This study aims to apply the Fuzzy Time Series (FTS) method to predict the increase in stunting cases at BKKBN North Sumatra. The FTS method is selected because it can handle data uncertainty and non-linear patterns, making it more effective in recognizing trends in stunting cases over time. The data used in this study were obtained from BKKBN North Sumatra, consisting of the number of stunting cases in 2023 and 2024 across 33 districts and cities. The research stages include data collection, fuzzification, fuzzy relation formation, defuzzification, and the implementation of the results into a web-based application using PHP programming and MySQL as the database. The results show that the Fuzzy Time Series method can effectively predict the upward and downward trends of stunting cases, where 16 districts/cities experienced an increase and 17 districts/cities experienced a decrease in stunting numbers for the following year. The developed system helps BKKBN analyze data more quickly, accurately, and efficiently. Therefore, the application of the Fuzzy Time Series method proves to be effective as a decision-support tool for planning prevention and mitigation programs for stunting in North Sumatra.]]>
