Jurnal Teknologi dan Sistem Komputer
Volume 8, Issue 2, Year 2020 (April 2020)

Segmentasi pelanggan menggunakan algoritme bisecting k-means berdasarkan model recency, frequency, dan monetary (RFM)

Novianti Puspitasari (Department of Informatics, Universitas Mulawarman)
Joan Angelina Widians (Department of Informatics, Universitas Mulawarman)
Noval Bayu Setiawan (Department of Informatics, Universitas Mulawarman)

Article Info

Publish Date
30 Apr 2020

Abstract

Information on customer loyalty characteristics in a company is needed to improve service to customers. A customer segmentation model based on transaction data can provide this information. This study used parameters from the recency, frequency, and monetary (RFM) model in determining customer segmentation and bisecting k-means algorithm to determine the number of clusters. The dataset used 588 sales transactions for PT Dinar Energi Utama in 2017. The clusters formed by the bisecting k-means and k-means algorithm were tested using the silhouette coefficient method. The bisecting k-means algorithm can form the best customer segmentation into three groups, namely Occasional, Typical, and Gold, with a silhouette coefficient of 0.58132.

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Journal Info
Jurnal Teknologi dan Sistem Komputer
Website

Abbrev

JTSISKOM

Publisher

Universitas Diponegoro

Subject

Computer Science & IT Electrical & Electronics Engineering

Description

Jurnal Teknologi dan Sistem Komputer (JTSiskom, e-ISSN: 2338-0403) adalah terbitan berkala online nasional yang diterbitkan oleh Departemen Teknik Sistem Komputer, Universitas Diponegoro, Indonesia. JTSiskom menyediakan media untuk mendiseminasikan hasil-hasil penelitian, pengembangan dan ...