<![CDATA[The amount of competition in the business world, especially in the car sales industry requires developers to find a strategy that can increase sales and marketing of products sold. Companies must pay attention to the type of product sales transactions both new products and old products which are marketed in various ways so as to improve the effectiveness of the company's performance in processing sales transaction data. Knowing the prediction results by looking at the accuracy of the C4.5 algorithm so that Honda car sales can obtain targets according to the planning that has been determined by the company. Secondary data used in this study are sales data of PT Prospect Motor Cikarang's sales executive. Forming a prediction model using the C4.5 method. In C4.5 algorithm, entropy and information gain calculations are performed where the best-selling attribute is the destination attribute, while the class, model, transmission, income, leasing, tenor and discount as source attributes to obtain root nodes and other nodes. Based on the results of the classification using the C4.5 algorithm shows that the accuracy reached 67.5%, which shows that the C4.5 algorithm is suitable for measuring sales predictions for sales of Honda cars. Keywords : Data Mining, Product Sale, Decision Tree, Algoritma C4.5.]]>
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