<![CDATA[Crude Palm Oil (CPO) production forecasting is an important element in supply chain management and company strategic planning. This study aims to forecast CPO production at PT Perkebunan Nusantara IV Regional 7 KSO using the Autoregressive Integrated Moving Average (ARIMA) method. Historical data of CPO production from 2017 to 2025 was analyzed using EViews 12 software. The analysis begins with data stationarity testing using the Augmented Dickey-Fuller (ADF) test. The selection of the optimal ARIMA model is determined based on the small Akaike Information Criterion (AIC), Schwarz Criterion (SC), and large R-squared values. After identifying and estimating the model, it is found that the ARIMA (1,0,0) model is the best model that can be used to forecast CPO production. This model has been tested with the Lijung-Box Test and White Noise Test, which shows that the residuals are random, so it is valid for forecasting.The forecasting results show a pattern of fluctuations in CPO production from year to year, with an increase in production in certain periods. This forecasting is expected to be a reference for companies in preparing the Company's Work Plan and Budget (RKAP) and optimizing production strategies to deal with changes in demand.]]>
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