Published: 2022-03-04
Sentimen Analisis Masyarakat Indonesia di Twitter Terkait Metaverse dengan Algoritma Support Vector Machine
DOI: 10.35870/jtik.v6i4.569
Ali Ahmad, Windu Gata
Article Metrics
- Views 0
- Downloads 0
- Scopus Citations
- Google Scholar
- Crossref Citations
- Semantic Scholar
- DataCite Metrics
-
If the link doesn't work, copy the DOI or article title for manual search (API Maintenance).
Abstract
Metaverse is part of the increasingly rapid development of technology in the world, bringing the virtual world into the real world is very possible. Starting from a novel, metaverse has now begun the process of being implemented, especially with the COVID-19 pandemic being one of the strong foundations for speeding up the implementation of this technology. Since the emergence of the metaverse echoed by Facebook, which has changed its name to meta, has made the world's public attention increasingly highlight this technology, some have welcomed it and some have concerns about the development of this technology. Research to explore the sentiments of the Indonesian people towards metaverse technology uses the CRISP-DM method with the Support Vector Machine algorithm and the test is carried out by comparing it with another algorithm, namely the tree algorithm, the programming language used is the R language with the Rstudio application. This study obtained the results of Indonesian public opinion on metaverse technology which showed 66% to be neutral, 17% negative and 16% positive, while the results of testing with the SVM algorithm showed SVM performance results of 87% with the kernel used was Linear, and these results are far better than using the tree algorithm which only has a performance of 71%.
Keywords
Metaverse ; Sentiment Analysis ; SVM
Article Metadata
Peer Review Process
This article has undergone a double-blind peer review process to ensure quality and impartiality.
Indexing Information
Discover where this journal is indexed at our indexing page to understand its reach and credibility.
Open Science Badges
This journal supports transparency in research and encourages authors to meet criteria for Open Science Badges by sharing data, materials, or preregistered studies.
How to Cite
Article Information
This article has been peer-reviewed and published in the Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi). The content is available under the terms of the Creative Commons Attribution 4.0 International License.
-
Issue: Vol. 6 No. 4 (2022)
-
Section: Computer & Communication Science
-
Published: %750 %e, %2022
-
License: CC BY 4.0
-
Copyright: © 2022 Authors
-
DOI: 10.35870/jtik.v6i4.569
AI Research Hub
This article is indexed and available through various AI-powered research tools and citation platforms. Our AI Research Hub ensures that scholarly work is discoverable, accessible, and easily integrated into the global research ecosystem. By leveraging artificial intelligence for indexing, recommendation, and citation analysis, we enhance the visibility and impact of published research.
-
CNN Indonesia, “Mengenal Sejarah Internet,” CNN INDONESIA, 2019. https://www.cnnindonesia.com/teknologi/20190312125646-185-376484/mengenal-sejarah-internet (accessed Jan. 16, 2021).
-
-
-
-
-
-
Fahmi Ahmad and Yuliawati, “Tren Kerja 2022, Makin Digital dan Fleksibel dengan Metaverse,” katadata.com. https://katadata.co.id/yuliawati/digital/61c99850ec00c/tren-kerja-2022-makin-digital-dan-fleksibel-dengan-metaverse (accessed Jan. 16, 2022).
-
C. Newton, “MARK IN THE METAVERSE,” www.theverge.com, 2021. https://www.theverge.com/22588022/mark-zuckerberg-facebook-ceo-metaverse-interview.
-
Jagokata.com, “Kamus Besar Bahasa Indonesia.” https://jagokata.com/arti-kata/.
-
-
-
-
-
Techvidvan, “SVM in R for Data Classification using e1071 Package,” https://techvidvan.com/t, 2022. https://techvidvan.com/tutorials/svm-in-r/ (accessed Jan. 17, 2022).
-
-
-
-
R. Prakoso, “Positif and Negative Word,” 2020. https://github.com/ramaprakoso/analisis-sentimen/blob/master/kamus/ (accessed Jan. 17, 2021).

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Authors who publish with this journal agree to the following terms:
1. Copyright Retention and Open Access License
Authors retain copyright of their work and grant the journal non-exclusive right of first publication under the Creative Commons Attribution 4.0 International License (CC BY 4.0).
This license allows unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
2. Rights Granted Under CC BY 4.0
Under this license, readers are free to:
- Share — copy and redistribute the material in any medium or format
- Adapt — remix, transform, and build upon the material for any purpose, including commercial use
- No additional restrictions — the licensor cannot revoke these freedoms as long as license terms are followed
3. Attribution Requirements
All uses must include:
- Proper citation of the original work
- Link to the Creative Commons license
- Indication if changes were made to the original work
- No suggestion that the licensor endorses the user or their use
4. Additional Distribution Rights
Authors may:
- Deposit the published version in institutional repositories
- Share through academic social networks
- Include in books, monographs, or other publications
- Post on personal or institutional websites
Requirement: All additional distributions must maintain the CC BY 4.0 license and proper attribution.
5. Self-Archiving and Pre-Print Sharing
Authors are encouraged to:
- Share pre-prints and post-prints online
- Deposit in subject-specific repositories (e.g., arXiv, bioRxiv)
- Engage in scholarly communication throughout the publication process
6. Open Access Commitment
This journal provides immediate open access to all content, supporting the global exchange of knowledge without financial, legal, or technical barriers.