INDONESIAN CONSUMER PRICE INDEX (CPI) FORECASTING USING AN EXPONENNTIAL SMOOTHING-STATE SPACE MODEL

Jauharul Maknunah, Mohamad As'ad, Sigit Setyowibowo, Eni Farida, Indah Dwi Mumpuni

Abstract

Abstract: CPI (consumer price index) is one of the economic measurement tools that can explain or inform about the development of prices for services/goods consumed or used by consumers. The CPI is related to determining inflation, therefore the CPI and inflation are important variables in viewing the economic conditions of a particular country or city. Current month inflation depend on previous CPI and current CPI. The CPI and inflation are so important that many researchers are studying inflation and the CPI. The purpose of this research is to predict the value of Indonesia's monthly CPI with a simple, easy, and highly accurate forecasting model using open-source software. The data used are monthly CPI data from the Central Statistics Agency (BPS) for January 2014 to August 2024. The benchmark for the best ETS model is based on the minimum value of the Akaike information criteria (AIC) and Bayesian information criteria (BIC). The best model obtained is the ETS (M, N, N) model with a smoothing parameter (α) of 0.9933, has a root mean square error (RMSE) of 3.275868 and a mean absolute percentile error (MAPE) of 0.6595211%. Keywords: Price Consumer Index (PCI), Forecasting of Indonesia PCI, Exponential Smoothing-State Space, ETS (M,N,N).

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