The Cluster Analysis of Online Shop Product Reviews Using K-Means Clustering

Data Science: Journal of Computing and Applied Informatics

View Publication Info
 
 
Field Value
 
Title The Cluster Analysis of Online Shop Product Reviews Using K-Means Clustering
 
Creator Nainggolan, Rena
Eviyanti Purba
 
Subject Data Mining, K-Means Clustering, Cluster, Online Customer Reviews
 
Description Technological developments have made changes in people's lifestyles, namely changes in the behavior of people who had shopped directly or offline to online. Many benefits are obtained from shopping online, namely the many conveniences offered by shopping online, besides that there are also many disadvantages of shopping online, namely the many risks in using e-commerce facilities, namely the problem of product or service quality, safety in payments, fraud. This research aims to mine review data on one of the e-commerce sites which ultimately produces clusters using the K-Means Clustering algorithm that can help potential customers to make a decision before deciding to buy a product or service
 
Publisher Talenta Publisher
 
Date 2020-07-31
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
 
Identifier https://talenta.usu.ac.id/JoCAI/article/view/2855
10.32734/jocai.v4.i2-2855
 
Source Data Science: Journal of Computing and Applied Informatics; Vol. 4 No. 2 (2020): Data Science: Journal of Computing and Applied Informatics (JoCAI)
2580-829X
2580-6769
 
Rights Copyright (c) 2020 Data Science: Journal of Computing and Applied Informatics
https://creativecommons.org/licenses/by-nc-nd/4.0
 

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