<![CDATA[Market Basket Analysis (MBA) is a data mining approach used to identify association patterns between products in transaction data. This approach is useful for retail companies in understanding consumer purchasing behavior and designing targeted marketing strategies. This study aims to analyze consumer purchasing patterns at PT XYZ, a household and snack retail company, using the FP-Growth algorithm. The data consists of 1,200 customer transactions from January to March 2025. The FP-Growth algorithm was applied with a minimum support of 5% and a confidence level of 60%. The analysis results show product combinations with strong associations, such as "Instant Noodles" → "Sachet Sauce" (support: 0.15; confidence: 0.82; lift: 1.35), and "Bottled Drinks" → "Light Snacks" (support: 0.13; confidence: 0.79; lift: 1.31). These patterns indicate two purchasing scenarios: routine and impulsive, which can be utilized for cross-selling, bundling, product placement, and promotional strategies. These findings provide a basis for optimizing stock management and data-driven decision making.]]>
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