Business Intelligence using the K-Nearest Neighbor Algorithm to Analyze Customer Behavior in Online Crowdfunding Systems

Business Intelligence using the K-Nearest Neighbor Algorithm to Analyze Customer Behavior in Online Crowdfunding Systems

Customer behavior classification can be useful to assist companies in conducting business intelligence analysis. Data mining techniques can classify customer behavior using the K-Nearest Neighbor algorithm based on the customer's life cycle consisting of prospect, responder, active and former....

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Bibliographic Details
Main Authors: Syadzali Chashif, Suryono Suryono, Endro Suseno Jatmiko
Format: Article
Language:English
Published: EDP Sciences 2020-01-01
Series:E3S Web of Conferences
Subjects:
classification
data mining
k-nearest neighbor
business intelligence
user segmentation
customer life cycle
customer relationship management
Online Access:https://www.e3s-conferences.org/articles/e3sconf/pdf/2020/62/e3sconf_icenis2020_16005.pdf

Internet

https://www.e3s-conferences.org/articles/e3sconf/pdf/2020/62/e3sconf_icenis2020_16005.pdf

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