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Submitted
Jan 20, 2025
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Dec 25, 2025
Published
Dec 30, 2025
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Abstract

The Consumer Price Index (CPI) is a measure of development success and inflation rates in a country. The CPI is often used to assess the general rate of increase in the prices of goods and services and as a consideration in adjusting salaries, wages, pensions, and other contracts. Therefore, forecasting the CPI is very useful for formulating future policies, including in the health sector. This study aims to create a CPI forecasting model for the health sector in East Java using the ARIMA-GARCH model, namely the integration of the ARIMA model with the GARCH model. The data used were monthly CPI data from January 2020 to December 2023 obtained from the Central Statistics Agency (BPS). The ARIMA model is used to capture long-term trends, while the GARCH model is applied to handle residual heteroscedasticity. The identification results showed that the best ARIMA model is ARIMA(2, 2, 2) with all coefficients statistically significant but heteroscedasticity occurs in the therefore, GARCH modeling is applied to the residuals. Based on the lowest Akaike Information Criterion (AIC) value of 8.342491, the GARCH(1,0) model was selected as the best model. The combined ARIMA(2,2,2)–GARCH(1,0) model produced an AIC value of 18.583 and an RMSE of 0.251383. Residual diagnostic tests indicated that the resulting model meets the assumptions of normal distribution and homogeneity, and there is no significant autocorrelation. The results of this study are expected to contribute to providing predictive information that can be used by the government as a reference in formulating health sector policies, particularly regarding managing the prices of goods and services to maintain economic stability in East Java.

Keywords

ARIMA-GARCH Model Consumer Price Index Forecasting Residual Heteroscedasticity

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How to Cite
Banat, I. B., Ira Yudistira, Wintan Konitania, & Kuzairi. (2025). FORECASTING MODEL FOR THE DYNAMICS OF THE CONSUMER PRICE INDEX IN THE HEALTH SECTOR IN EAST JAVA USING THE ARIMA-GARCH MODEL. Parameter: Journal of Statistics, 5(2), 68-75. Retrieved from https://bestjournal.untad.ac.id/index.php/parameter/article/view/17627

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