<![CDATA[In an era of increasingly fierce retail competition, optimizing product layout and sales strategies is a matter of urgency for businesses seeking to maintain and increase revenue. CV. Tolong Kita Jaya, a building materials store, is currently facing challenges in determining an effective product placement strategy and has not yet maximized its cross-selling potential. This is due to a lack of analysis of past consumer purchasing patterns, resulting in frequent missed opportunities to sell related products. Therefore, this study aims to address this issue by implementing a data mining approach. This study employs the comprehensive Cross-Industry Standard Process for Data Mining (CRISP-DM) framework, ranging from business understanding to the evaluation stage. For modeling, this study implements Market Basket Analysis (MBA) using the Apriori algorithm. This model was specifically chosen to extract association rules from a set of historical transaction data to identify relationships among building materials that are frequently purchased together. The test results from this modeling revealed several product combinations with high and valid support, confidence, and lift ratio metrics. The key findings of this study provide a strategic foundation for redesigning retail layouts, in which items with strong associations are positioned in close proximity. Furthermore, these findings facilitate the formulation of actionable cross-selling strategies by management, such as the creation of promotional sales bundles, which are ultimately projected to increase the overall sales volume of building materials.]]>
