Inflation Forecasting for East Kalimantan Province Using Hybrid Singular Spectrum Analysis- Autoregressive Integrated Moving Average Model

Authors

  • Melisa Arumsari Universitas Mulawarman
  • Sri Wahyuningsih
  • Meiliyani Siringoringo

DOI:

https://doi.org/10.20956/j.v18i1.14284

Keywords:

ARIMA, Forecasting, Hybrid, Inflation, SSA

Abstract

The Singular Spectrum Analysis (SSA)-Autoregressive Integrated Moving Average (ARIMA) hybrid method is a good combination of forecasting methods to improve forecasting accuracy and is suitable for economic data that tends to have trend and seasonal patterns, one of which is inflation data. The purpose of this study is to obtain the results of inflation forecasting for East Kalimantan Province in 2021 using the SSA-ARIMA hybrid model. The results of the inflation forecasting for East Kalimantan Province in 2021 using the SSA-ARIMA(1,1,1) hybrid model overall experienced an increase and the highest inflation in 2021 occurred in December of 0.92% with a forecasting accuracy level based on the Root Mean Square Error (RMSE) was 0.069399 and Mean Absolute Percentage Error (MAPE) was 32.61084%  

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Published

2021-09-02

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Section

Research Articles