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SEGMENTASI LAYANAN INTERNET BANKING

Jurnal Manajemen dan Kewirausahaan: Volume 4, Nomor 2, Desember 2016
Journal from JIPTUNMERPP / 2017-08-16 11:06:33
Oleh : Ellen Theresia Sihotang, Faculty of Economics Merdeka University Malang (Ellen@perbanas.ac.id)
Dibuat : 2016-12-01, dengan file

Keyword : Segmentation, Clustering, Internet Banking, Consumer Behaviour
Url : http://drive.google.com/file/d/0B0uNqoBLtJGvRDBnRnVZRW1RbWM/view?usp=sharing

The purpose of this study is to analyze internet bankingÂ’s users based on their experiences. It can be used to set marketing program of internet banking that appropriate with customers needs, in order to anticipate tight competition. This research methods starts with focus group discussion and clustering analysis to classify 312 respondents of internet banking users based on demographic, benefit and behavioral segmentation. The sampling method uses purposive sampling and snowball sampling. K-Means Clustering methodÂ’s produces four optimal clusters. The benefit orientation of the first cluster in on time saving. Second cluster, concern on the ease of getting and operating internet banking so this cluster does not need auxiliary features such as video guide to use internet banking. The third clusterÂ’s orientation is on the modern lifestyle and the ease of getting and operating internet banking service with detailed daily mutation transaction The fourth cluster, concerns on the detailed daily mutation transaction but they are not sure with the security of personal data via internet banking.

Deskripsi Alternatif :

The purpose of this study is to analyze internet bankingÂ’s users based on their experiences. It can be used to set marketing program of internet banking that appropriate with customers needs, in order to anticipate tight competition. This research methods starts with focus group discussion and clustering analysis to classify 312 respondents of internet banking users based on demographic, benefit and behavioral segmentation. The sampling method uses purposive sampling and snowball sampling. K-Means Clustering methodÂ’s produces four optimal clusters. The benefit orientation of the first cluster in on time saving. Second cluster, concern on the ease of getting and operating internet banking so this cluster does not need auxiliary features such as video guide to use internet banking. The third clusterÂ’s orientation is on the modern lifestyle and the ease of getting and operating internet banking service with detailed daily mutation transaction The fourth cluster, concerns on the detailed daily mutation transaction but they are not sure with the security of personal data via internet banking.

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PropertiNilai Properti
ID PublisherJIPTUNMERPP
OrganisasiF
Nama KontakDra. Wiwik Supriyanti, SS
AlamatJl. Terusan Halimun 11 B
KotaMalang
DaerahJawa Timur
NegaraIndonesia
Telepon0341-563504
Fax0341-563504
E-mail Administratorperpus@unmer.ac.id
E-mail CKOwsupriyanti@yahoo.com

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  • Editor: Wiwik Supriyanti, Dra. SS.