<![CDATA[Laptops are one of the basic needs in today's modern life. Laptops are used in a wide variety of activities such as work, study, and entertainment. This research aims to be able to predict the class of laptops in the Ilda Computer store. In this process, the K-Nearest Neighbor Algorithm (KNN) method will be applied. There are 2 types of data that will be used in this study, namely training data totaling 80 data and test data as many as 6 data. In the data, there are 7 criteria that will be used, namely Price, Screen Size, Resolution, OS, RAM, Processor Type, and Laptop Class. In this study, it was obtained that the application of the KNN Algorithm can help in determining the prediction of the Laptop Class. And also the application of the KNN algorithm with K=3 obtained the best performance results with an accuracy value of 50%, a presicion of 50%, and a recall of 66%. Meanwhile, with K=4, the best performance results were obtained with an accuracy value of 50%, presicion of 66%, and recall of 50%. Finally, the K=5 obtained the best performance with an accuracy value of 66%, a presicion of 33%, and a recall of 100%.]]>
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