<![CDATA[This study aims to analyze the application of the Autoregressive Integrated Moving Average (ARIMA) and Seasonal Autoregressive Integrated Moving Average (SARIMA) methods for forecasting rim wheel production demand that can be used at PT Surteckariya Indonesia. The ARIMA and SARIMA methods are forecasting techniques that utilize time series data. Forecasting was conducted using rim wheel shipment data over 21 months from January 2023 to September 2024. This data was used to forecast the next 12 periods, namely October 2024 to September 2025. This research compares the best forecasting method between the two approaches to ensure accurate results for predicting production demand at PT Surteckariya Indonesia. The results of this study using the ARIMA method yielded the best model ARIMA(1,0,0), while for the SARIMA method, the best model was (1,0,0)(1,0,0)12. A comparison of the ARIMA and SARIMA forecasting methods showed a smaller MAPE value for ARIMA, at 0.869. This aligns with the normality test, where ARIMA meets the criteria while SARIMA does not. Therefore, the ARIMA method is more suitable for forecasting rim wheel shipment data at PT Surteckariya Indonesia.]]>
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