International Journal of Artificial Intelligence Research
Vol 4, No 1 (2020): June

Comparison Analysis of K-Nearest Neighbor and Naïve Bayes in Determining Talent of Adolescence

Yessi Jusman (Scopus ID : 35810354700 Universitas Muhammadiyah Yogyakarta, Indonesia)
Widdya Rahmalina (Department of Informatics Engineering, Faculty of Engineering, Universitas Abdurrab, Pekanbaru, Riau)
Juni Zarman (Department of Informatics Engineering, Faculty of Engineering, Universitas Abdurrab, Pekanbaru, Riau)



Article Info

Publish Date
19 Feb 2020

Abstract

Adolescence always searches for the identity to shape the personality character. This paper aims to use the artificial intelligent analysis to determine the talent of the adolescence. This study uses a sample of children aged 10-18 years with testing data consisting of 100 respondents. The algorithm used for analysis is the K-Nearest Neigbor and Naive Bayes algorithm. The analysis results are performance of accuracy results of both algorithms of classification. In knowing the accurate algorithm in determining children's interests and talents, it can be seen from the accuracy of the data with the confusion matrix using the RapidMiner software for training data, testing data, and combined training and testing data. This study concludes that the K-Nearest Neighbor algorithm is better than Naive Bayes in terms of classification accuracy.

Copyrights © 2020






Journal Info

Abbrev

IJAIR

Publisher

Subject

Computer Science & IT Electrical & Electronics Engineering

Description

International Journal Of Artificial Intelligence Research (IJAIR) is a peer-reviewed open-access journal. The journal invites scientists and engineers throughout the world to exchange and disseminate theoretical and practice-oriented topics of Artificial intelligent Research which covers four (4) ...