PENENTUAN PRODUK UNGGULAN ONLINE SHOP MENGGUNAKAN K-MEANS DAN SUBTRACTIVE CLUSTERING:

Abstract

Clustering is a method to search and classify data that has similarity characteristics between one data with other data. This clustering implementation can be applied to various fields as an example in terms of determining best-selling products. One method of clustering is often used because of its relatively quick and adaptable is the K-Means algorithm. Technique of grouping K-means method is very needed by Nasa Jambionline shop to classify their products. During this time Nasa Jambi online shop classifies the product by way of checking through sales memos and report books to find out and calculate the best-selling product. This is not efficient because the time required to calculate and check the notes and reports is long enough. Use of the K-means method will make it easier in clustering best-selling products Nasa Jambi online shop. The time needed to cluster the products will be shorter because the calculations and checks are done computerized. Data input that will be used is the number of products sold, the amount of the transaction and the remaining stock of products. The data process begins by making a calculation of the K-Means method according to the existing stages by determining the number of groups, centroid centers, to generate output in the form of product classification.