| dc.description.abstract | CV XYZ is a business engaged in the food sector, located in Medan, Indonesia. The company often experiences stockouts of their product, which is catfish skin crackers. The main cause of this issue is the stockout of their primary raw material, which is catfish skin. This study aims to design a dashboard that can forecast the demand for catfish skin in order to avoid stockouts that could lead to lost sales. The forecasting methods used are Linear Regression and Double Exponential Smoothing, which are compared based on the lowest error value. The error values are calculated using the Mean Absolute Deviation (MAD), Mean Squared Error (MSE), and Mean Absolute Percentage Error (MAPE) methods. The forecasting calculations are then implemented into a forecasting dashboard so that the calculations can be used continuously. The results of the study show that the Linear Regression method produces higher forecasting accuracy compared to the Double Exponential Smoothing method, with a MAD value of 25.0932, an MSE value of 960.4652, and a MAPE value of 0.6320%, which are lower than those of the Double Exponential Smoothing method, which has a MAD value of 49.4993, an MSE value of 4,236.71, and a MAPE value of 1.2498%. | en_US |
