Comparison of RAM Classification with Decision Tree Algorithms and KNN

Abstract

A laptop is a rather small personal computer consisting of a keyboard, screen, microprocessor and usually a rechargeable battery. In the current era of technology, when buying a laptop, we need to have thorough and detailed considerations regarding our needs in using a laptop, especially laptop RAM. By comparing Decision Tree and KNearest Neighbors algorithm, a more accurate algorithm was found to make a prediction in buying a laptop with suitable variable consideration. The result shows that Decision Tree algorithm is more accurate to be used in predicting the suitable laptop RAM. Decision Tree accuracy is 68%, this result is higher than KNN accuracy which is only 66%.