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ABSTRACT

LOYAL CUSTOMER ANALYSIS USING K-MEANS CLUSTERING AT RIZKY ACCESSORIES

By : Wulandari (21.22.0368)

Rizky Accessories has been experiencing a continuous decline in sales due to the emergence of new competitors. To address this issue, the owner of Rizky Accessories aims to identify loyal customers, who are believed to contribute to long- term business growth. This study seeks to classify loyal customers by implementing the K-Means Clustering method, which is a part of data mining, using the LRFM (Length, Recency, Frequency, Monetary) model. This model helps segment customers based on their transaction patterns to determine their level of loyalty. Customer transaction data is collected, analyzed, and processed using clustering techniques to categorize customers into different segments. The findings of this study are expected to provide valuable insights for the owner of Rizky Accessories to enhance customer loyalty through strategies such as discounts, reward programs, or personalized marketing approaches. By implementing the right strategies, Rizky Accessories is expected to retain and increase the number of loyal customers, ensuring sustainable and stable business growth.
Keywords: K-Means Clustering; Loyal Customers; Data Mining; LRFM.