<![CDATA[Purpose: This study aims to address the underutilization of transaction data in the outdoor equipment rental industry by developing an integrated Business Intelligence (BI) dashboard using the FP-Growth algorithm to generate product bundling recommendations and support data-driven decision-making. Methods: A quantitative approach based on the Knowledge Discovery in Databases (KDD) framework was employed using 596 rental transactions from Batas Outdoor Rental recorded between January and May 2026. The data were preprocessed and transformed into a binary matrix using TransactionEncoder. FP-Growth was applied with a minimum support of 2% (0.02), while association rules were generated using a minimum confidence of 30% (0.30) and validated with a lift threshold of 1.20. Results: A quantitative approach based on the Knowledge Discovery in Databases (KDD) framework was employed using 596 rental transactions from Batas Outdoor Rental recorded between January and May 2026. The data were preprocessed and transformed into a binary matrix using TransactionEncoder. FP-Growth was applied with a minimum support of 2% (0.02), while association rules were generated using a minimum confidence of 30% (0.30) and validated with a lift threshold of 1.20. Novelty: This study integrates FP-Growth-based transaction analysis with an interactive BI dashboard specifically for outdoor equipment rentals. Unlike previous studies focusing primarily on product combinations or promotional packages, the proposed approach provides an end-to-end decision-support framework connecting transaction analysis, automated bundling recommendations, and interactive visualization.]]>
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