Prediction Of Purchase Of Goods Using The Average Single Moving Method Case Study Store LADIES.ID

Abstract

Technological developments are very rapid, one of which is the use of the internet and online systems contained therein. One system that continues to be developed and its benefits are felt is the decision support system. Decision support systems are very helpful in making a decision or finding the best solution, Ladies.id stores still record sales of goods manually. Purchases of goods are carried out manually, resulting in an accumulation of stock due to the purchase of too many items. In this study using the Single Moving Average method by comparing the calculations of 3, 4 and 5 orders, while for the calculation of errors using RMSE (Root Mean Squared Error) and also MAPE (Mean Absolute Squared Error). The results of the sample calculation of the pants of this study are by calculating using 3 orders, the RMSE result is 41.3797 and the MAPE is 37.1934. Then by using the calculation of 4 orders, the RMSE results are 38.2624 and MAPE is 34.8641 and the last calculation using 5 orders results in RMSE results of 39.6775 and MAPE of 36.8851. The conclusion is that calculations using 4 orders get the smallest results so it can be concluded that 4 orders are the best recommendations for predicting the next trousers purchase. Every item in the Ladies.id store uses calculations of 3, 4 and 5 orders to get results, from these calculations are compared and the results that have the smallest RMSE and MAPE values that will be used for the next purchase recommendation.