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This is a Quantitative Study study.

October 20, 2025TelematikaOpen Access

Implementation of the Random Forest algorithm to predict rice needs in DKI Jakarta

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Rice needs were successfully predicted using the random forest algorithm, achieving an accuracy of 0.63.
The evaluation metrics included a Mean Squared Error of 207.86 and a Mean Absolute Error of 9.43.
Data from BAPANAS and Cipinang Main Market were utilized to model rice demand over time.
Collaborative efforts between government and universities aim to enhance food processing efficiency in the region.

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Analysis predicts rice needs in DKI Jakarta with Mean Squared Error 207.86, highlighting food processing collaboration.

Santoso et al. (2025) studied this question.

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