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A rating system or reviews are generally used to assist in making decisions. Rating systems widely used as a technique in recommending items to customers, one of which used in recommending resorts to be used by customers. However, the credibility of the rating looks vague because the rating could only represent some points of service. So that customer preference with each other is very different. Personalized recommendation systems offer more personalized advice, precisely knowing the preferences or tastes of the customers. Especially for customers who have a transaction history or reservation as at their resorts provide useful information used by managers to design a recommendation model for their customers. In this study aims to create a model of resort recommendations based on a rating of frequency. This frequency is the number of the resort used by the customer within the specified time frame. With the frequency can represent the preferences of customers. The RFM (Recency, Frequency, and Monetary) method is used to measure the reservation frequency value of the customer. The K-Means method is used to categorize customer data with its frequency and classify the type of resort. Recommendation resort to the customer based on the dominant use in one of the resort types. The type of resort recommended for customers base on the similarity between the type of resort used and other types of resorts.

GURILEM : A Novel Design of Customer Rating Model using K-Means and RFM