<![CDATA[Abstract— Hotel is one of the business entities that have the potential to grow and develop which requires a lot of investment that stands both in the middle of the city and in tourist destination areas. Hotel room reservations can be made by customers before they use the hotel via online media, but the problem that occurs is that customers who have made room bookings can cancel orders for various reasons, so that hoteliers feel a loss because the cancellation can provide opportunities for designers to get these customers. This study uses the Naïve Bayes Algorithm as an algorithm that can produce high accuracy and can process a lot of data, and backward selection as the selection of suitable parameter values to improve accuracy. This study uses 10,000 hotel room customer data with accuracy results using the Naïve Bayes Algorithm of 89.67%, and accuracy results using the Naïve Bayes Algorithm and Backward Elemination Feature Selection of 97.83%. Prediction Results Check-Out, Canceled and No-Show.Keywords: Prediction, Booking Room Hotel, Naïve Bayes, Backward Elemination.]]>
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