Rice production is one of the main indicators of national food security, especially in Indonesia.Accurate rice production forecasts are essential to support strategic planning and decision-makingin the agricultural sector. This study aims to apply fuzzy logic using the Mamdani method toforecast rice production in 2024. This method was chosen for its ability to handle the uncertaintyand complexity of data that often occurs in agricultural systems. The variables used includeharvest area, productivity, rainfall, and average temperature. The data analyzed is historical datafrom several previous years, which is then processed using a fuzzy inference system. The predictionprocess was carried out in several stages, namely fuzzification, rule formation, inference, anddefuzzification. The results of the study indicate that the Mamdani fuzzy logic model predicts riceproduction in 2024 to be 27,100,000 tons; it is hoped that this model will provide predictions thatclosely align with historical data and trends, with a relatively small margin of error. Thus, thismethod can be a reliable and adaptive tool in supporting future rice production planning and policy.
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