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

Abstract

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.

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