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

International Journal of artificial intelligence research

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Title Comparison Analysis of K-Nearest Neighbor and Naïve Bayes in Determining Talent of Adolescence
Creator Jusman, Yessi
Rahmalina, Widdya
Zarman, Juni
Subject Science; Artificial Intelligence; Computer; Information; System
Adolescence; Algorithms; Naïve Bayes; K-Nearest Neighbor; Classification; Dataset
Description 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.
Publisher STMIK Dharma Wacana
Contributor Universitas Muhammadiyah Yogyakarta
Date 2020-02-19
Type info:eu-repo/semantics/article
Peer-reviewed Article
Format application/pdf
Source International Journal of Artificial Intelligence Research; Vol 4, No 1 (2020): June; 39-48
Language eng
Rights Copyright (c) 2020 International Journal of Artificial Intelligence Research

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