Penerapan Algoritma K-Means Dalam Klasterisasi Penjualan Laptop

Abstract

Laptops are indispensable both for students and for office workers because of their advantages compared to desktop computers. With the development of today's laptop era, there are various brands and specifications that sometimes make people have difficulty and difficulty in finding, choosing or buying the right laptop and according to their needs. Therefore, the purpose of this study is to determine the grouping of laptops that will be purchased by consumers using the K-Means algorithm method and to find out the relationships and clustering that can provide information to determine sales patterns for laptop sellers according to customer needs. Based on the results of the tests that have been carried out in this study, the K-Means algorithm shows a new insight, namely the grouping of laptop sales based on 3 clusters. Cluster 1 is a laptop sales category with low or Low specifications, namely 217 of 1000 laptop sales categories based on the specifications of the laptop being tested, then cluster 2 is a laptop sales category with medium or medium specifications, which is 286 of 1000 laptop sales categories based on the specifications of the laptop being tested, and the last is cluster 3 which is a category of laptop sales with fairly high specifications or High, namely 497 out of 1000 laptop sales categories based on the specifications of the laptop being tested.

Keywords: Laptop, Data Mining, The k-Means algorithm.