Prediction of the price of broilers in the future is intended to control the excess and shortage of broiler stock can be minimized. When the price of purebred chicken can be predicted accurately, the fulfillment of consumer demand can be managed on time. This study aims to analyze the prediction accuracy of broiler prices using the Single Exponential Smoothing (SES) method compared to using the linear regression method, so that a more accurate method will be obtained to predict the price of broilers. The percentage of prediction error values is the most important criterion in analyzing the prediction accuracy of these two methods. The results showed that the average percentage of error in predicting the quantity of sales of broilers using the SES method with the smoothing parameter value =0.5 is the method that has the highest predictive accuracy (MAPE=0.00258%) compared to using the linear regression method (MAPE= 0.05%).
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