Open AccessPENENTUAN TINGKAT MINAT BELANJA ONLINE MELALUI MEDIA SOSIAL MENGGUNAKAN METODE CLUSTERING K-MEANS
Author(s) -
Anita Anita
Publication year - 2018
Publication title -
rang teknik journal
Language(s) - English
Resource type - Journals
eISSN - 2599-2090
pISSN - 2599-2082
DOI - 10.31869/rtj.v1i2.758
Subject(s) - social media , cluster analysis , advertising , computer science , similarity (geometry) , internet privacy , world wide web , business , artificial intelligence , image (mathematics)
Social media becomes the pre-eminent businessperson in marketing the goods. This is based on the increasing use of social media from year to year. The determination of the level of interest in online shopping through social media aims to help find out which social media are in demand in online shopping. In this study the data used are social media BBM Group, Instagram, Facebook, Twitter and Whatsapp and age and gender. In determining the level of online shopping interest one method of Data Mining used is the method of Clustering K-Means. Clustering is the process of dividing data into classes or clusters based on their similarity. To assist in data processing used Rapid Miner application that is able to provide information on the level of interest in online shopping in social media