<![CDATA[In the digital era, transaction data analysis plays a crucial role in strategic decision-making, especially for SMEs such as Toko Adzmi Art in Cirebon Regency. This study aims to develop a sales data association model using the FP-Growth algorithm to identify product association patterns. Daily transaction data over a year were collected, processed through data cleaning, standardization, and transformation, and analyzed using RapidMiner software. Minimum support and confidence parameters were applied to evaluate the frequency and strength of product relationships. The results show that the combination of "Photocopy" and "Passport Photo" services has a confidence of 0.491 and a support of 0.061, with "Photocopy" as the most in-demand product (support 0.497). These findings open opportunities for bundling strategies and inventory optimization to enhance operational efficiency. This model provides an empirical foundation for SMEs to leverage data mining technology to improve competitiveness and customer satisfaction.]]>
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