In every manufacturing business activity, policies that must be implemented properly are generally considered, such as inventory management, to minimize costs and minimize profits. Therefore, inventory forecasting is necessary to estimate production needs. However, in reality, the Gunungsitoli PLKT Business has not yet implemented inventory forecasting. The purchase of raw materials does not match raw material usage, resulting in a shortage of required inventory. This makes the business overwhelmed in making repeat purchases, coupled with limited raw material suppliers and low profits. The purpose of this study is to determine and analyze the forecasting of raw material inventory needs using the time series method in the PLKT Business, as well as to determine and be able to maximize raw material inventory to achieve the expected profit.The type of research used in this study is quantitative research based on data on the use of raw materials, in this case Simalambuo wood, in the PLKT Business for the period January 2024 – July 2025. The methods used for time series model forecasting are the moving average and exponential smoothing methods. From the forecasting results using the moving average method, it was obtained that for forecasting wood raw material inventory with an MSE (Mean Squared Error) error value of 30.36. While the forecasting results using the exponential smoothing method were obtained that for forecasting wood raw material inventory with an MSE (Mean Squared Error) error value of 29.21 for α = 0.1, an MSE (Mean Squared Error) error value of 36.92 for α = 0.5, and an MSE (Mean Squared Error) error value of 50.70 for α = 0.9. So, the smallest forecasting error value is the exponential smoothing method with α = 0.1 and is highly recommended for PLKT Business because it is very suitable and precise, in addition, by carrying out inventory forecasting it helps businesses to save raw material inventory as much as 32 m^3 from the remaining use of raw materials and can maximize it in the storage warehouse so that there is no shortage in the coming month. This also resulted in a significant increase in operating profit of Rp. 132,000,000.00 from the COGS calculation after forecasting was carried out.
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