| dc.description.abstract | This research is about to forecast the demand of shipment, with the purpose to determining the number of vehicles needed to fulfill the demand’s customer. In forecasting the demand of shipment are divided into several periods namely period in a day, week and month. To determine the number of vehicles, two parameters are used namely demand data and different capacities of vehicle. Based on determination of number vehicles, a scenario are build when demand data increase and when decrease. If the demand increase and availability of vehicles are not sufficient, then it is necessary to having lease a vehicle or making a scenario of double shift job. The method use in this research are ARIMA and Holt’s Exponential Smoothing, both methods will be compared. Selection of two methods are made due to similarity in patterns of the demand data and to compared the best forecasting results. The results of this study indicate to use ARIMA method better that Holt’s, so in determining number of vehicles generate that the data demand periode per day still require to leasing the vehicle to fulfill the demand of shipment. While the demand data periode per week and month can be fulfilled by applying double shift scenario. | en_US |
