Keywords:-

Keywords: Consumer Price Index; SARIMA; Forecasting; Intervention Analysis; Step Function; SMAPE

Article Content:-

Abstract

The state of the country's economy can be analyzed based on the economic data of some countries, one of the data closely related to the state of the country's economy is the CPI (Consumer Price Index). The Consumer Price Index is the main indicator used to measure a country's inflation. The consumer price index was in a very downward trend from January 2020 to January 2023. The change in the consumer price index was due to the Covid-19 epidemic. Changes in CPI data are responded to by intervention analysis, where forecasting of future conditions is done with intervention analysis. Interference analysis is time series data that is affected by external and internal factors that can cause changes in the model at the same time. The intervention model has 2 functions, namely step and pulse functions. The step function is an intervening phenomenon that produces long-term effect, while the pulse function is an intervening phenomenon that produces short-term (temporary) effect. The research data variable taken is the monthly data of the Indonesian CPI for the period January 2014 to January 2023. The data uses a step function intervention model because there is an extreme decline in the period January 2020 (T = 73) to January 2023 (T = 109) in a long period of time. The resulting intervention model is SARIMA(0,1,1)(0,0,1)12 in order b=0, s=0, and r=1 with a model accuracy using SMAPE of 0,58% which shows the model is classified as very good.

References:-

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Harefa, F. J. S., ., T., & Maruddani, D. A. I. (2024). Step Function Intervention Analysis on Indonesia’s Consumer Price Index (CPI). International Journal Of Mathematics And Computer Research, 12(11), 4586-4591. https://doi.org/10.47191/ijmcr/v12i11.06