Comparison of RAM Classification with Decision Tree Algorithms and KNN

Solehudin Al Ayyubi (Universitas Pembangunan Nasional “Veteran” Jawa Timur)
Indira Setia Amalia (Universitas Pembangunan Nasional “Veteran” Jawa Timur)
Amalia Anjani Arifiyanti (Universitas Pembangunan Nasional “Veteran” Jawa Timur)

PELS (Procedia of Engineering and Life Science)
Vol 2 No 2 (2022): Proceedings of the 4th Seminar Nasional Sains 2022

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%.