PERBANDINGAN METODE K-NEAREST NEIGHBOR DAN METODE DECISION TREE PADA SISTEM REKOMENDASI LAPTOP

ALWIN, MUHAMMAD IZDIHAR (2024) PERBANDINGAN METODE K-NEAREST NEIGHBOR DAN METODE DECISION TREE PADA SISTEM REKOMENDASI LAPTOP. Undergraduate thesis, UPN Veteran Jawa Timur.

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Abstract

A laptop is a device that has a small size and saves power. Currently, laptops are widely used by people in activities that use the internet. With the advancement of technology that continues to grow, the demand for technology is also getting higher. However, not everyone knows the indicators in the selection of laptop products according to personal preference and criteria for laptop needs, with the variety of laptop specifications available on the market. To overcome this problem, a laptop recommendation system has been developed. There are many types of algorithms that can be used in recommendation systems. Some of them are K-Nearest Neighbor and Decision Tree. In this study, researchers conducted a comparative analysis of the two methods to determine the performance of each algorithm on the laptop recommendation system. From the test results, the results obtained in the form of the Decision Tree algorithm are superior with an average accuracy rate of 61%. While the K-Nearest Neighbor algorithm has an accuracy rate of 52%.

Item Type: Thesis (Undergraduate)
Contributors:
ContributionContributorsNIDN/NIDKEmail
Thesis advisorADITIAWAN, FIRZA PRIMANIDN0023058605firzaprima.if@upnjatim.ac.id
Thesis advisorAL HAROMAINY, MUHAMMAD MUHARROMNIDN0701069503muhammad.muharrom.if@upnjatim.ac.id
Subjects: Q Science > QA Mathematics > QA76.6 Computer Programming
Q Science > QA Mathematics > QA76.87 Neural computers
T Technology > T Technology (General)
Divisions: Faculty of Computer Science > Departemen of Informatics
Depositing User: Muhammad Izdihar Alwin
Date Deposited: 19 Jan 2024 02:20
Last Modified: 19 Jan 2024 02:20
URI: http://repository.upnjatim.ac.id/id/eprint/19819

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