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September 10, 2025Agro Bali Agricultural JournalOpen Access

Analysis of Food Security Index Predictions in Indonesia using Machine Learning Approach

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Authors

FSFrederic Morado SaragihWWWahyu Catur Wibowo

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Overview

Analysis reveals xgboost forecasts food security index scores accurately, indicating improved prediction methods are essential.

Key Points

  • The xgboost method predicts food security index scores in Indonesia with an R2 value of 0.912.
  • Evaluation metrics show the xgboost method outperforms other models, including ensemble machine learning for food security predictions.
  • Root mean square error and mean absolute error metrics highlight effective forecasting methods for Indonesia's food security index.
  • Future predictions suggest Indonesia's food security index score will reach 75.56 in 2025, showcasing a trend based on current data.

Cite This Study

Saragih et al. (2025) studied this question.

synapsesocial.com/papers/68c1b81254b1d3bfb60ebf30https://doi.org/10.37637/ab.v8i2.2302
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