FORECASTING WITH WEIGHTED MOVING AVERAGE METHOD FOR PRODUCT PROCUREMENT STOCK - Amali Amali; Gatot Tri Pranoto; Muhammad Darwis (Jurnal Sistem Informasi dan Sains Teknologi, 2022)
ABSTRACTDhanty Store is a family start-up located in East Jakarta. It was initiated in 2018, engaged in retail with the main product in the form of women's clothing and accessories. One of the important processes in Dhanty Store operations is the product procurement process. Currently, Dhanty Store request products according to their wishes without looking at their sales data. This causes their product stock is not well controlled. When there is a lot of demand, sometimes Dhanty Shops run out of stock so their customers will move to other stores. In addition, the process of requesting and procuring products to suppliers also takes a long time so that it can further disrupt the operations of Dhanty Store. This study develops a forecasting application prototype with the Weighted Moving Average method to assist Dhanty Store in the process of requesting and procuring their products. Forecasting results in the period (t) of the 1st week of January were 275 products. In addition, this study predicts product stock with a 4-week moving average and the MAD tracking signal value is ranged from -1.51 to 3.86 and the MAPE value is 35.4%. As for the reliability and level of user acceptance of the prototype model in this study, tested using the System Usability Scale (SUS) method and it is known that the average value given by respondents was 82 with details 0% considered inappropriate, 40% considered neutral and 60% rated it according to need.                                                                                                                                                        Keywords: data mining, forecasting, weighted moving average, MAD, MAPE, SUS