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What is LSTM Model for Predicting Indonesian Inflation about?

Our research evaluates the effectiveness of the long short-term memory (LSTM) model in forecasting annual year-on-year (YoY) inflation across 82 cities in Indonesia based on time series data from BPS economic reports for 2014-2024. This study tests the accuracy of the model in reconstructing past inflation patterns, then evaluates the capabilities and limitations of the model in various urban area contexts with the root mean square error (RMSE), mean absolute percentage error (MAPE), and coefficient of dete

Author

IAES IJAI

Language

EN