<![CDATA[Purpose : to build collaborative partners between government institutions and universities in food processing, especially rice, by predicting rice needs in the DKI Jakarta area.Design/methodology/approach:The approach in this research uses the Random Forest algorithm which functions to predict rice needs in the DKI Jakarta area.Results: rice demand prediction application with evaluation values Mean Squared Error 207.86, Mean Absolute Error 9.43, MAPE 0.048, Root Mean Squared Error 14.4, accuracy 0.63Originality/value/state of the art:research using data from BAPANAS, Cipinang Main Market, with 2 datasets of rice stock, population, year and rice consumption using a random forest algorithm to predict rice needs in the DKI Jakarta area ]]>
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