Performance of Synthetic Minority Over-sampling Technique on Support Vector Machine and K-nearest Neighbor for Sentiment Analysis of Metaverse in Indonesia
Year: 2024
Type: article
Abstract: The metaverse is one of the most discussed things on social media, Twitter in Indonesia. This view can be both positive and negative in Indonesian society, hence the need for sentiment analysis. However, creating a sentiment classification model with unbalanced data will reduce performance. For this reason, Synthetic Minority Oversampling is needed in Support Vector Machine and K-Nearest Neighbor algorithms. The results of Synthetic Minority Oversampling can improve the accuracy of the Support Vector Machine and K-Nearest Neighbor algorithms.
Source: Proxies Jurnal Informatika
Authors: Roy Antonio, Hironimus Leong
Institution: Soegijapranata Catholic University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4402006538