A contest of sentiment analysis: K-nearest neighbor versus neural network

Kurniawan, Fachrul ORCID: https://orcid.org/0000-0002-3709-8764 and Supriyatno, Triyo ORCID: https://orcid.org/0000-0002-6833-4555 (2025) A contest of sentiment analysis: K-nearest neighbor versus neural network. IAES International Journal of Artificial Intelligence (IJ-AI). Indonesia. ISSN 2252-8938

Preview

Text 23813.pdf - Published Version Available under License Creative Commons Attribution Share Alike. Download (329kB) | Preview

Abstract

Discourse about public matters often encompasses sentences that address topics emerging within societal contexts, including issues related to Islamophobia. Debates surrounding this subject frequently evoke support and opposition within digital platforms and interpersonal interactions. Categorizing such dialogic expressions within online media facilitates an evaluation of their negative and positive implications. This study employs two distinct methodologies, specifically deep learning and machine learning techniques, to visualize the findings by implementing dual algorithms. According to the comparative analysis, deep learning achieves a higher accuracy rate of 78%, whereas machine learning achieves a rate of 71%. Thus, deep learning is a better method for textual data classification.

Item Type:	Journal Article
Keywords:	Classification; Deep learning; K-nearest neighbor; Machine learning; Neural network
Subjects:	08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing 08 INFORMATION AND COMPUTING SCIENCES > 0803 Computer Software 08 INFORMATION AND COMPUTING SCIENCES > 0899 Other Information and Computing Sciences
Divisions:	Faculty of Technology > Department of Informatics Engineering
Depositing User:	Fachrul Kurniawan
Date Deposited:	11 Jun 2025 08:10

Downloads

Origin of downloads

Actions (login required)

View Item