Customer Segmentation Analysis and Healthy Brand Sales Potential Using K-Means Clustering,RFM,Decision Tree and Swot Analysis at PT. Sukanda Djaya
Analisis Segmentasi Pelanggan dan Potensi Penjualan Healthy Brand Menggunakan K-Means Clustering,RFM,Decision Tree dan Analisis SWOT pada PT. Sukanda Djaya
DOI:
https://doi.org/10.21070/ups.11475Keywords:
k-means clustering, RFM, customer segmentation, healthy brand, , SWOT, data miningAbstract
This study aims to analyze customer segmentation and predict the sales potential of healthy brands at PT Sukanda Djaya during the COVID-19 pandemic period using a data mining approach. The method implemented is K-Means Clustering, integrated with the Recency, Frequency, Monetary (RFM) model and SWOT analysis to support strategic decision-making. The data used in this study are secondary sales data from the food service sector from 2020 to 2024. The results indicate that the clustering process produced very good quality, with silhouette score values ranging from 0.94 to 0.96. Customer segmentation successfully identified customer groups with high and low profit potential. The Diamond brand consistently dominated most clusters, reflecting strong brand performance and high customer loyalty. Meanwhile, other healthy brands such as Oatside and V-Soy still faced challenges in competing with non-healthy brands in several segments. In addition, negative values were found in billing quantity, indicating product return activities and potential issues in the supply chain. The integration of clustering results with SWOT analysis shows that the company is positioned in Quadrant I, which represents a growth strategy. This indicates that the company has strong internal strengths and significant market opportunities. Therefore, the recommended strategies include strengthening healthy brand positioning, product innovation, and distribution optimization to improve the company’s competitiveness. This study contributes by integrating analytical and strategic approaches to support data-driven decision-making
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