Comparison of ARIMA and Linear Trend Forecasting Models for Product X at PT ABC
DOI:
https://doi.org/10.33379/gtech.v8i2.4075Keywords:
Forecating, Time Series, ARIMA, Trend LinearAbstract
Forecasting is market-oriented product planning, capacity management, and subsequent production. The deviation (error) value as the error, between the forecasted value and the actual value is used to assess the reliability of one forecasting model against another. When compared to other medium-term forecasting techniques, the ARIMA (Autoregressive Integrated Moving Average) model provides fairly accurate forecasting results. The purpose of this research is to prove the assumptions of the forecasting model and determine the forecasting value for the next period with a case study of PT ABC producing powdered beverage product x. This research uses Minitab software as a calculation tool. The data used is the demand for product x for the period January 2021 to December 2023. The results of this study indicate that the ARIMA (1,1,1) model is a suitable model for PT ABC's demand forecasting model. The error value of the ARIMA (1,1,1) model is smaller than other forecasting models, including the Linear Trend model. These results confirm that the ARIMA model is the most effective one to use for the following year.
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