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The use of Business Intelligence (BI) systems as decision support systems in the automotive environment, especially luxury cars, is still limited to support decision making regarding production and distribution policies. Forecasting is an important tool in planning for every organization and agency in need. The purpose of this study is to design BI that can be applied to luxury car show rooms as part of the automotive business organization by utilizing existing information systems. This research can also be used to see an overview of luxury car sales patterns using clustering techniques using K-Means algorithms. This study was designed by relating data on fuel increases from previous years. The results of this study are in the form of forecasting data using the smothing holtwinters method of luxury car sales in the next 5 years by adjusting to the conditions of fuel increase in the next 5 years for the process of making predictions of luxury car needs in Indonesia in the coming period.
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