<![CDATA[This research was conducted at PT. Socfindo Kebun Mata Pao is one of the industrial companies engaged in palm oil processing. The main raw material used in processing Crude Palm Oil (CPO) is Fresh Fruit Bunches (FFB), where the FFB used must be based on good characteristics to get quality CPO. PT. Socfindo Kebun Mata Pao needs to pay attention to the adequacy of raw materials or the shortage of FFB raw materials. If the FFB inventory exceeds the amount of production needed, it will certainly cause additional storage costs and a decrease in the quality of CPO. Meanwhile, if the FFB supply is too small, it will increase procurement costs and interfere with the smooth running of products, resulting in inefficient production activities. Therefore, companies need to forecast the need for FFB raw materials, to minimize the occurrence of excess or shortage of FFB. The methods used in forecasting the needs of FFB raw materials are the Linear Regression method and the Quadratic method. The purpose of this study is to obtain forecasting results with the best accuracy between the Linear Regression and Quadratic methods to be able to predict the need for FFB raw materials in the 2022 period and so that companies can manage FFB raw material inventory by production needs. The data collection method was used from the observations and study documents results. The forecasting results from the calculation of the error rate in the Linear Regression method obtained a Standard Error of Estimate (SEE) of 317.16 and a Mean Absolute Percentage Error (MAPE) of 0.58%, while the error rate in the Quadratic method obtained a Standard Error of Estimate (SEE) of 323.55 and a Mean Absolute Percentage Error (MAPE) of 4.75%. From the calculation of the error rate in both methods, the smallest error rate is obtained in the Linear Regression method.]]>
