Penerapan Logika Fuzzy Metode Mamdani dalam Memprediksi Hasil Produksi Beras di Indonesia Tahun (2024)
Pendekatan Berbasis Variabel Luas Panen, Curah Hujan, dan Suhu
DOI:
10.29303/jm.v8i2.11638Published:
2026-06-16Downloads
Abstract
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-making
in the agricultural sector. This study aims to apply fuzzy logic using the Mamdani method to
forecast rice production in 2024. This method was chosen for its ability to handle the uncertainty
and complexity of data that often occurs in agricultural systems. The variables used include
harvest area, productivity, rainfall, and average temperature. The data analyzed is historical data
from several previous years, which is then processed using a fuzzy inference system. The prediction
process was carried out in several stages, namely fuzzification, rule formation, inference, and
defuzzification. The results of the study indicate that the Mamdani fuzzy logic model predicts rice
production in 2024 to be 27,100,000 tons; it is hoped that this model will provide predictions that
closely align with historical data and trends, with a relatively small margin of error. Thus, this
method can be a reliable and adaptive tool in supporting future rice production planning and policy.
Keywords:
Fuzzy Logic Mamdani Method Rice Production Prediction Fuzzy Inference System Indonesian AgricultureReferences
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