<![CDATA[This research aimed to develop forecasting models for both the production and producer prices of cassava in Central Java using the Autoregressive Integrated Moving Average (ARIMA) method, recognizing the significant role of this commodity in the regional economy. Through time series analysis stages using 1993 until 2022 data years encompassing stationarity testing (ADF), model identification based on Autocorrelation Function (ACF) and Partial (Autocorrelation Function) PACF, parameter estimation using Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC) atau Schwarz Bayesian Criterion (SBC), standard error with Stata 17, and residual diagnostic testing (white noise), the study identified ARIMA (2,1,1) as the optimal model for production forecasting and ARIMA (1,1,1) for producer price forecasting. The forecasting results indicate a declining trend in cassava production in Central Java from 1993 to 2029, contrasting with an increasing trend in producer prices. Supply elasticity analysis using the forecasted production and price data yielded a value of -0.76, indicating that the supply of cassava in Central Java is inelastic, where price changes do not elicit a proportional supply response from farmers. Although cassava is an inelastic and inferior commodity, the government still needs to play an active role in improving farmers' knowledge of technology and encouraging processing research to increase its added value and supply chain effectiveness.]]>
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