Electric Vehicle Sales-Prediction Application Using Backpropagation Algorithm Based on Web

Abstract

The accuracy of predicting future product sales is needed to minimize losses and gain profits. Inventory of goods carried out manually or improper product inventory planning causes the number of goods to accumulate due to the small number of requests, so the goods are damaged. Therefore, a sales prediction system with high accuracy is needed to assist in stocking electric vehicles. This research aimed to predict electric vehicle sales using the web-based backpropagation method. This study uses the backpropagation method to predict electric vehicle sales data from 2015 to 2022. The data is divided into 84 instances as training data and 12 instances as testing data. The result of this study was that the backpropagation method obtained a MAPE error rate of 6.25%. Thus, the backpropagation method can be used for predicting electric vehicle sales because it has a very accurate performance level.