Abstract: the basic principles of using data mining in a Business Intelligence (BI) environment to gain knowledge about business. This of course raises business competition between companies. Data mining is intended to provide solutions for decision makers in the business world to develop their business. To see the business world that is most sought after by the wider community. The benefits facilitate the analysis of large data and help provide information on data that is processed. One method contained in data mining used in this study is the Clustering method. The results of this study are the applications that are built can help the business world as a picture in making decisions in order to get the pattern of sales or marketing of products. Keywords: Data mining, Business Intelligence, Clustering. Abstrak: prinsip dasar penggunaan data mining dalam lingkungan Business Intellegence (BI) untuk mendapatkan pengetahuan tentang bisnis. Hal tersebut tentu saja menimbulkan persaingan bisnis antar perusahaan. Data mining dimaksudkan untuk memberikan solusi bagi para pengambil keputusan didunia bisnis untuk mengembangkan bisnis mereka. Untuk melihat dunia bisnis yang paling banyak diminati masyarakat luas. Manfaatnya mempermudah analisis data yang besar dan membantu memberikan informasi data yang diolah. Salah satu metode yang terdapat dalam data mining yang digunakan dalam penelitian ini adalah metode Clustering (Pengelompokkan). Hasil dari Penelitian ini adalah Aplikasi yang dibangun dapat membantu dunia bisnis sebagai gambaran dalam pengambilan keputusan dalam rangka mendapatkan pola penjualan atau pemasaran produk. Kata Kunci: Data mining, Business Intellegence, Clustering.DAFTAR PUSTAKAKahaner, L. (1997). Competitiveintelligence: how to gather, analyze, and use information to move your business to thetop. Simon & Schuster.Liautaud, B., & Hammond, M. (2000). Ebusinessintelligence: turning informationinto knowledge into profit. McGraw-HillProfessional.Luhn, H. P. (1958). A business intelligencesystem, IBM Journal of Research andDevelopment, 2(4), 314―319.Chang, E., Dillon, T., & Hussain, F. (2006).Trust and reputation for service-orientedenvironments: technologies for buildingbusiness intelligence and consumerconfidence.Cody, W. F., Kreulen, J. T., Krishna, V., &Spangler, W. S. (2002). The integration ofbusiness intelligence and knowledge.Dhar, V., & Stein, R. (1997). Seven methods for transforming corporate data into business intelligence. Prentice Hall Upper Saddle River, NJ.