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The implementation of Customer Relationship Management (CRM) on textile supply chain using k-means clustering in data mining

机译:在数据挖掘中使用K-Mearing集群在纺织供应链上实施客户关系管理(CRM)

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Supply chain in textile industry requires an involvement of several other related industry therefore it divide into several sub-sector industry. The market dynamic and complexity of supply chain network are causing problem. This study aims to classify the market base on consumers behaviour through their preferences in textile product in East Java. Analysis of data using data mining approach. Algorithm K-means type clustering is use as clustering methods by integrating with Customer Relationship Management (CRM) concept. The simulation result of data set using five cluster depends on their variability value are Lumajang, Malang, Madura, Tulungagung, and Ponorogo. The clusters formed have the highest importance predictor in “way of purchase” and the lowest in “purchase flexibility”. The result in this study is generally indicate that consumers of textile products in East Java prioritize values in customer value compared to product quality.
机译:纺织业供应链需要参与其他几个相关产业,因此它分为几个子部门产业。供应链网络的动态和复杂性导致问题。本研究旨在通过在东爪哇纺织产品的纺织产品偏好来对消费者行为进行分类。使用数据挖掘方法分析数据。算法K-means类型聚类通过与客户关系管理(CRM)概念集成来使用作为聚类方法。使用五个群集的数据集的仿真结果取决于它们的可变性值是Lumajang,Malang,Madura,Tulungagung和Ponorogo。形成的集群具有“购买方式”的重要性预测因素,最低的“购买灵活性”。本研究的结果通常表明,与产品质量相比,东爪哇省东爪哇纺织产品的消费者优先考虑客户价值。

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