<![CDATA[Rice is a staple food crop in Indonesia, including in West Sumatra Province, which plays an important role in national food security. This study aims to develop a rice production prediction model using Artificial Neural Networks (ANN) with the Backpropagation algorithm. Historical rice production data from 2006 to 2023 in 19 regencies/cities in West Sumatra Province were used as the data basis. The research methods include data collection from BPS West Sumatra, data preprocessing, prediction process using the Backpropagation algorithm, and accuracy testing of the prediction results. The results show that ANN with the Backpropagation algorithm can predict rice production with an accuracy rate of 82.56% using an architecture with 16 neurons in the input layer, 9 neurons in the hidden layer, and 1 neuron in the output layer. This prediction model is expected to assist farmers and the government in planning optimal rice production, thereby increasing production and the welfare of farmers in West Sumatra Province. Thus, this research provides significant contributions in supporting decision-making in the agricultural sector, particularly in efforts to enhance food security and the welfare of farmers in the region]]>
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