Analysis of Algorithms Support Vector Machine with Naive Bayes Kernel in Data Classification

Juanto Simangunsong, Tulus, Muhammad Zarlis

2019

Abstract

This research is about SVM and Naive Bayes in data mining. Many researchers carry out and develop methods to improve the accuracy and classification of data in good results. This research was carried out by conducting experiments on the types of flowers. In this study, it was concluded that the performance of Naïve Bayes was better than Support Vector Machine, Naïve Bayes had excellent results that promised to help classify the best values to get data grouping. This research is better than SVM. The training process has a difference of 28% and a testing process of 0.83% with the accuracy.

Paper Citation

in Harvard Style

Simangunsong J., Zarlis M. and Tulus. (2019). Analysis of Algorithms Support Vector Machine with Naive Bayes Kernel in Data Classification.In Proceedings of the International Conference on Natural Resources and Technology - Volume 1: ICONART, ISBN 978-989-758-404-6, pages 287-291. DOI: 10.5220/0008553302870291

in Bibtex Style

@conference{iconart19,
author={Juanto Simangunsong and Muhammad Zarlis and Tulus},
title={Analysis of Algorithms Support Vector Machine with Naive Bayes Kernel in Data Classification},
booktitle={Proceedings of the International Conference on Natural Resources and Technology - Volume 1: ICONART,},
year={2019},
pages={287-291},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008553302870291},
isbn={978-989-758-404-6},
}

in EndNote Style

TY - CONF

JO - Proceedings of the International Conference on Natural Resources and Technology - Volume 1: ICONART,
TI - Analysis of Algorithms Support Vector Machine with Naive Bayes Kernel in Data Classification
SN - 978-989-758-404-6
AU - Simangunsong J.
AU - Zarlis M.
AU - Tulus.
PY - 2019
SP - 287
EP - 291
DO - 10.5220/0008553302870291