Data-Driven Strategies for Fuel Distribution in Indonesia: A case Study of PT Pertamina Patra Niaga
Strategi Distribusi Bahan Bakar di Indonesia Berbasis Data: Studi Kasus di PT Pertamina Patra Niaga
DOI:
https://doi.org/10.21070/ups.3895Keywords:
churn, customer segmentation, salesman clustering, decision tree, k-means clusteringAbstract
PT Pertamina as a key supplier in Indonesia's competitive fuel market. To maintain its market edge, PT Pertamina must understand and predict customer behavior and loyalty. This study uses a combination of the RFM method, decision tree algorithms, and k-means clustering to analyze customer loyalty, salesperson performance, and potential customer churn, with a focus on the relationship between churn and salesperson expertise. The research utilizes sales transaction data from PT Pertamina Patra Niaga Regional Jatimbalinus. Findings from the decision tree algorithm show a high loyalty rate among customers, with 100% confusion matrix. Salespersons are categorized into two performance-based clusters: 'good performance' and 'poor performance'. A key discovery is the identification of a customer group likely to churn, a factor not influenced by salesperson performance. Understanding these aspects can help the company refine its strategies, potentially reducing churn and bolstering its position in the fuel market.
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