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Ensemble Methods for Indonesian Inflation Forecasting by Yuana Sukmawaty is a document available to read on EtoBox.

This document summarizes a study that developed models for forecasting inflation in Indonesia using ARIMA, artificial neural networks (ANN), and ensembles of both methods. It finds that a single ANN model produced the best forecasts for the next 12 months based on national and regional inflation data from 2000-2012. Among ensemble methods that combined multiple models, an ANN ensemble performed best with the lowest error compared to ARIMA or combined ANN-ARIMA ensembles. The goal was to help Bank Indonesia

Author

Yuana Sukmawaty

Language

EN