Clustering Customer Data Using Fuzzy C-Means Algorithm

PIKSEL (Penelitian Ilmu Komputer Sistem Embedded dan Logic)

View Publication Info
Field Value
Title Clustering Customer Data Using Fuzzy C-Means Algorithm
Creator Nurfaizah, Nurfaizah
Fathuzaen, Fathuzaen
Description The pattern of the service industry is influenced mostly by economic growth. When economic growth rises, the economic activity will also grow as in the case of insurance activities. One of the assets owned by an insurance company is the customer, hence the existence of a loyal or potential customer should be maintained by the insurance company. This study focuses on clustering or grouping the existing customer data in insurance companies using the Fuzzy C-Means (FCM) algorithm. This study uses data from the company for analysis and the results can be used as a basis for insurance companies in making decisions, especially those related to further insurance marketing to customers who have participated in insurance or who are still actively registered in payment insurance. Fuzzy C-Means can be used for clustering the customer datasets. It obtained 3 clustering results using Partition Coefficient (PC) in determining the validity index and the centers value was ranged from 0.5 to 1.0.
Publisher LPPM Universitas Islam 45 Bekasi
Date 2021-03-24
Type info:eu-repo/semantics/article
Format application/pdf
Source PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic; Vol 9 No 1 (2021): Maret 2021; 1 - 14
Language eng
Rights Copyright (c) 2021 PIKSEL : Penelitian Ilmu Komputer Sistem Embedded and Logic

Contact Us

The PKP Index is an initiative of the Public Knowledge Project.

For PKP Publishing Services please use the PKP|PS contact form.

For support with PKP software we encourage users to consult our wiki for documentation and search our support forums.

For any other correspondence feel free to contact us using the PKP contact form.

Find Us


Copyright © 2015-2018 Simon Fraser University Library