数据挖掘的应用使用了k -手段来定义案例研究客户:UD。农业肥料

Sari Indah, Fati Gratianus Nafiri Larosa, Yolanda Y. P. Rumapea
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引用次数: 0

摘要

UD。Penyubur Tani是一家贸易公司,为农民经营农业业务出售各种必需品,如化肥、杀虫剂、种子等。UD。Penyubur Tani希望通过给予折扣形式的奖励来增加客户忠诚度,从而使其业务越来越受信任和增长,但在给予客户奖励方面仍然没有效果,因为UD。Penyubur Tani很难逐一计算出哪些客户的购买频率和总购买价格最属于非常忠诚和忠诚的类别。因此,需要一个应用程序来对客户进行分类,以便确定在目标上建立忠诚度的策略。通过使用CRM的概念和K-Means方法,从数据处理中获得的结果能够将必须优先考虑的客户分组,并可以确定哪些客户值得奖励。从100个客户数据中,K-Means聚类方法成功地将非常忠诚的标准分组为8%,忠诚34%,潜在58%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
PENERAPAN DATA MINING MENGGUNAKAN METODE K-MEANS UNTUK PENENTUAN REWARD PELANGGAN Studi Kasus: UD. Penyubur Tani
UD. Penyubur Tani is a trading business that sells various kinds of needs for farmers in running their business in agriculture such as fertilizers, pesticides, seeds, and others. UD. Penyubur Tani wants to increase customer loyalty by giving rewards in the form of discounts so that its business is increasingly trusted and increasing, but in giving rewards to customers is still not effective, because UD. Penyubur Tani has difficulty in calculating one by one which customers whose frequency of purchases and total purchase price are most in the category of very loyal and loyal. Therefore, an application is needed to classify customers so that in determining strategies in building loyalty on target. By using the concept of CRM and the K-Means method, the results obtained from data processing are able to group customers who must be prioritized and can determine which customers deserve a reward. From 100 customer data, the K-Means Clustering method succeeded in grouping very loyal criteria by 8%, loyal 34% and potential by 58%.
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