A study on demand forecasting in textile industry

Numerous operation decision are based on the proper forecast of future demand. For this reason, textile industry considered forecasting is crucial process for effectively guiding several activities. The objectives of this research are to identify demand forecasting method applied by the company, to analyses the sales data using several forecasting method and to propose the most suitable forecasting method to the company. The forecasting method involves in this study is Time Series Forecasting Method. The forecasting method was analyzed by using forecast error measurement tools includes Mean Absolute Deviation (MAD), Mean Squared Error (MSE), Mean Absolute Percentage Error (MAPE) and Tracking Signal to monitor the forecast result of various method. The result of this study showed that the Additive Decomposition (Seasonal) of forecasting method is the most suitable method to apply and proposed to the textile Industry. This method comes out With the accurate result and least forecast error