Penerapan Metode Clustering Dalam Segmentasi Pelanggan Perusahaan Logistik

Abstract

Marketing is important in business to compete and maintain market share. The development of technology brings major changes in the industry. In addition to product development as well as required services, and customer segmentation becomes a factor to consider in marketing strategies. Clustering, such as the K-Means method, is used in customer segmentation to divide data into groups based on similarities. This technique helps in useful pattern recognition and customer segmentation. By applying Clustering techniques in Data mining, companies can understand customer behavior, recognize similar customer groups, and plan marketing strategies accordingly. The results showed that the best cluster was generated with a k value of 4, and the data was normalized using the Min-Max Normalization method. Grouping customers in the form of clusters can enable the identification of consumer profiles to guide companies in decision making.