Analisis Tren Dinamika Harga Beras Premium di Tingkat Penggilingan Dengan Model ARIMA

Abstrak

This study aims to analyze and predict the price dynamics of premium quality rice at the milling level in Indonesia using the ARIMA time series model method. The data used are secondary data from the official publication of the Central Statistics Agency (BPS) for the period 2013–2023, in Rupiah per kilogram (Rp/Kg). This study uses a descriptive quantitative approach with analysis stages including stationarity testing using the Augmented Dickey-Fuller (ADF) Test, model identification through the Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF), and determining the best model based on the Akaike Information Criterion (AIC), Schwarz Criterion (SC), and the Ljung-Box residual test. The results show that premium rice price data is not stationary at the level, but becomes stationary after the first differentiation. The best model obtained is ARMA (1,1) with the highest R-Square value of 0.9719, the lowest AIC (-5.04), and random residuals (white noise). Based on forecasting results, the price of premium rice in 2024 is expected to remain stable with a downward trend, from Rp 9,502 in January to Rp 9,476 in December. These results indicate that the Indonesian rice market is relatively controlled without significant price spikes. These findings can inform the government's formulation of policies to control rice prices, balance the interests of farmers and consumers, and strengthen national food security.