Customer Loyalty Clustering Model Using K-Means Algorithm with LRIFMQ Parameters
| Main Author: | Utomo, Aloysius Matz Teguh |
|---|---|
| Format: | Article info application/pdf eJournal |
| Bahasa: | eng |
| Terbitan: |
Universitas Dr. Soetomo
, 2020
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| Subjects: | |
| Online Access: |
https://ejournal.unitomo.ac.id/index.php/inform/article/view/2691 https://ejournal.unitomo.ac.id/index.php/inform/article/view/2691/pdf https://ejournal.unitomo.ac.id/index.php/inform/article/downloadSuppFile/2691/559 https://ejournal.unitomo.ac.id/index.php/inform/article/downloadSuppFile/2691/560 https://ejournal.unitomo.ac.id/index.php/inform/article/downloadSuppFile/2691/561 https://ejournal.unitomo.ac.id/index.php/inform/article/downloadSuppFile/2691/575 |
Daftar Isi:
- Loyal customers are one of the factors that determine the development of a business. Therefore, businesses need a strategy to keep customers loyal, even making customers who were previously less loyal to become more loyal. The strategy used must be right on target according to customer segmentation. The purpose of this paper is to model a cluster of customer loyalty to help businesses in making the right decisions of marketing strategy. Segmentation is done using the k-means algorithm with LRIFMQ (length, recency, interval, frequency, monetary, quantity) as parameters, and the CLV (customer lifetime value) of each cluster is calculated. Data obtained from PT. XYZ (a company engaged in food processing) for one year (1 January 2019 - 31 December 2019), with 337.739 transactions, and 26.683 customers. AHP (analytical hierarchy process) method is used for LRIFMQ weighting because this method has a consistency index calculation. The silhouette coefficient is used to calculate the cluster quality and determine the optimal number of clusters. The best results are obtained with the silhouette coefficient value of 0,632904 with the number of clusters 6.
- Pelanggan yang loyal adalah salah satu faktor yang menentukan kemajuan suatu bisnis. Oleh karena itu, perlu suatu strategi untuk membuat pelanggan tetap loyal, bahkan membuat pelanggan yang sebelumnya kurang loyal menjadi lebih loyal. Strategi yang digunakan harus tepat sasaran sesuai dengan segmentasi pelanggan. Pada paper ini, segmentasi pelanggan dilakukan menggunakan algortima k-means dengan LRIFMQ (length, recency, interval, frequency, monetary, quantity) sebagai parameter, dan dihitung nilai CLV-nya (customer lifetime value) dari tiap kluster. Data didapatkan dari PT. XYZ (perusahaan yang bergerak di bidang pengolahan makanan) selama 1 tahun (1 Januari 2019 - 31 Desember 2019), sebanyak 337.739 transaksi, dan 26.683 pelanggan. Metode AHP (analytical hierarchy process) digunakan untuk pembobotan LRIFMQ. Silhoutte coefficientdigunakan untuk menghitung nilai kualitas kluster dan menentukan jumlah kluster optimal. Didapatkan hasil terbaik dengan nilai silhouette coefficient0,71616 dengan jumlah kluster 2, dan nilai CLV terbaik 0,77837.