When conducting sales analysis, one can do it from several angles, one of which is analyzing items that often appear and are purchased together by customers. Data mining techniques can be used to perform the analysis. The results of sales transactions produce a lot of sales data that can be used for analysis of sales of goods using the Market Basket Analysis method. The results of the application of the Market Basket analysis method can assist in making decisions in compiling a product catalog or the placement of goods because each item has interrelated properties and forms certain association rules. The placement of products that are not by consumer habits when buying products is a problem in this study. The algorithm used is the apriori algorithm with 18 categories of items. Each class of goods has a supporting value and certainty value. The application of these association rules can be taken into consideration for making decisions on effective marketing and sales strategies at Marzan Jaya Building Materials Stores. The results of this study show the highest support and confidence from the sand and cement groups with a support value of 0.025 and a confidence of 0.584 with a lift ratio of 4.962. This shows that buyers tend to buy sand and cement class. Researcher suggest for further research to add a comparison of the association algorithm with other algorithms