Forecasting the Inflation Rate in Lampung Province Using the ARIMA Method
DOI:
https://doi.org/10.32877/bt.v7i3.2335Keywords:
ARIMA , Forecasting , Inflation, Lampung Province , Time Series
Abstract
Inflation is one of the key indicators that reflects the economic stability of a region. Inflation instability can directly impact the purchasing power of the population, increase poverty rates, and create imbalances in macroeconomic policies. In Lampung Province, inflation fluctuations have become a significant issue requiring attention, particularly in the context of regional economic planning and policy-making. This study forecasts the inflation rate using the Autoregressive Integrated Moving Average (ARIMA) method, which is known to be effective in analyzing time series data and providing accurate short-term estimates. The data used comprises monthly inflation rates from 2006 to 2023, obtained from the Central Bureau of Statistics (BPS) of Lampung Province. Five ARIMA model configurations were tested: ARIMA(3,1,2), ARIMA(3,1,1), ARIMA(2,1,1), ARIMA(1,1,1), and ARIMA(5,1,1). Based on the evaluation of the Akaike Information Criterion (AIC) and Mean Absolute Percentage Error (MAPE), the ARIMA(1,1,1) model was identified as the best-performing model, with the lowest AIC value and a MAPE of 0.57. The model also passed diagnostic tests, including residual normality and white noise assessment using the Ljung-Box test. The forecasting results indicate a gradual upward trend in inflation, with predicted rates of 0.23% in January 2024, 0.29% in February 2024, and 0.30% in March 2024. These findings provide early indications that inflation in Lampung Province tends to increase in the short term, and can serve as a basis for formulating more targeted regional inflation control policies.
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