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All Journal International Journal of Artificial Intelligence Research
Zarman, Juni
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Computer Science & IT Electrical & Electronics Engineering

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Comparison Analysis of K-Nearest Neighbor and Naïve Bayes in Determining Talent of Adolescence Jusman, Yessi; Rahmalina, Widdya; Zarman, Juni
International Journal of Artificial Intelligence Research Vol 4, No 1 (2020): June
Publisher : Universitas Dharma Wacana

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (303.209 KB) | DOI: 10.29099/ijair.v4i1.118

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.
Co-Authors Jusman, Yessi Widdya Rahmalina, Widdya