Penerapan Data Mining dengan Metode K-Nearest Neighbor untuk Memprediksi Penjualan Aksesoris Aquarium

Abstract

PT. Surya Jaya Aquarium is an industry engaged in the sale of various types of aquarium accessories, such as aquarium machines, filter media, aquarium lights. Currently, PT. Surya Jaya Aquarium often lacks certain items when ordering goods from customers. Meanwhile, there is often an excess of other goods at the same time due to a lack of orders from customers. For this reason, it is necessary to carry out the process of predicting product sales at the company, so that the process of controlling product orders can be carried out. To carry out the prediction process, the K-Nearest Neighbor algorithm can be applied. The purpose of this algorithm is to classify new objects using features and training data samples. The data used in this study is sales data for aquarium accessories products sourced from sales for the last 3 years from 2020, 2021 and 2022 originating from PT. Surya Jaya Aquarium. After that the data is selected and will be used to be processed in predicting sales of aquarium accessories for the next period. The K-Nearest Neighbor technique is used in this study to model data that has been prepared using the Knowledge Discovery in Databases (KDD) stage. From the results of the tests carried out, information was obtained that the error rate (error) from the sales prediction results was 6,196%