<![CDATA[Business intelligence systems participate to deliveran accurate and useful information to decision makers in marketing division of bakeries manufacture. The purpose of this study was to design business intelligence model to analyze the marketing product, design the data mining model, measure and analyze the marketing process of the product they sell. The methodology of this research wasto analyze system requirements, design unified modeling language, make process extract, transform, and load, designdata warehouse, and data mining that integrated with the on line analytical process cube webbased. The business intelligence model produced was a marketing data mining model and on line analytical process cube. The result from on line analytical process cube was the data warehouse of transaction in R Bakery. In designing the data mining, K-means clustering method was used. The results from data mining k-means clustering were there were 83% cluster 1 and 17% cluster 2. Cluster 1 wasthecategorize for low leftover breads and cluster 2 was the categorize for high leftover breads. The model cube recency, frequency, and monetary and customer lifetime value resulted ranked out of the most amount of sales in R Bakery. Keywords: business intelligence system, data mining, extract transform load, on line analitical process cube]]>
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