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All Journal PELS (Procedia of Engineering and Life Science)
Indira Setia Amalia
Universitas Pembangunan Nasional “Veteran” Jawa Timur
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Engineering

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Comparison of RAM Classification with Decision Tree Algorithms and KNN Solehudin Al Ayyubi; Indira Setia Amalia; Amalia Anjani Arifiyanti
Procedia of Engineering and Life Science Vol 2 No 2 (2022): Proceedings of the 4th Seminar Nasional Sains 2022
Publisher : Universitas Muhammadiyah Sidoarjo

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (789.756 KB) | DOI: 10.21070/pels.v2i2.1200

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%.
Co-Authors Amalia Anjani Arifiyanti Solehudin Al Ayyubi