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Majalah Ilmiah Teknologi Elektro
Article . 2022 . Peer-reviewed
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Literature Review Analisis Perilaku Pelanggan Menggunakan RFM Model

Authors: Rukmi Sari Hartati; Ida Bagus Alit Swamardika; Putu Aryasuta Wicaksana;

Literature Review Analisis Perilaku Pelanggan Menggunakan RFM Model

Abstract

Abstract— Data is an asset for every company, especially Customer Data. Processing of customer data hereinafter can be referred to as Data Mining. The current tight competition in the industry makes companies have to be careful in processing their customer data, one of which is processing customer data for CRM operations. With the aim of recognizing customers by analyzing customer behavior. So this can be an investment for the company. Customer behavior can be predicted using the RFM model. And on this occasion, the author conducts a study on the implementation the RFM Model in data mining in helping companies to better understand their customers. From the results of the review, the RFM model in the 2016-2021 range, it is more combined with data mining techniques, namely the clustering algorithm, where the goal is to group or segment customers. And from the results of the review, the author also formulates research that can be done, namely combining the RFM model with the TOPSIS method.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
gold