Analisis Sentimen Mengenai Vaksin Sinovac di Media Sosial Twitter Menggunakan Metode Naïve bayes Classification
DOI:
https://doi.org/10.35870/jtik.v6i3.479Keywords:
Sentiment Analysis, Naïve bayes classification, Twitter, SinovacAbstract
The Sinovac vaccine is an example of a type of inactivated vaccine. The government bought Sinovac, Novavax, AstraZeneca, and Pfizer vaccines. This vaccine is used to treat the Covid-19 pandemic. This vaccine is used to treat the Covid-19 pandemic. The role of the Indonesian people in expressing and stating the pros and cons often involves public services that are easily accessible by many people, namely social media, one of which is Twitter. This can be used as material to analyze who produces data in support of decisions. The technique that can be used is sentiment analysis. The method used in this study is the Naïve bayes Classification. The purpose of this study was to determine the value of sentiment analysis on the Sinovac vaccine using the Naive Bayes Classification method on Twitter social media using Indonesian. The result of this research is the final probability value based on the condition 0.000002765 for positive and 0.000000359 for negative. A response with a positive comment has a greater probability of a response with a negative comment.Downloads
References
Susilo, A., C. martin R., dkk. 2020. Coronavirus Disease 2019: Tinjauan Literatur Terbaru. Jurnal Ilmu Penyakit Dalam Indonesia, Vol. 7, No. 1.
Kementerian Kesehatan Republik Indonesia. 2021. Faktor Kunci Triple-helix Menuju Keberhasilan Vaksinasi Covid-19. Infodatin Pusat Data dan Informasi Kementerian Kesehatan Republik Indonesia, ISSn 2442-7659.
Nugroho, Agung. 2018. Analisis Sentimen pada Media Sosial Twitter Menggunakan Naive Bayes Classifier dengan Ekstraksi Fitur N-Gram. Jurnal Ilmu Komputer & Informatika (J-SAKTI), Jilid (2) No.2.
Astari, Ni Made A J., Dewa G H D., & Gede I. 2020. Analisis Sentimen Dokumen Twitter Terkait Dampak Virus Corona Menggunakan Metode Naive Bayes Classifier. Jurnal Sistem dan Informatika, Vol 15, No 1.
Ikasari, D., Yuliana F., & Widiastuti. 2020. Analisis Sentimen dan Klasifikasi Tweet Bahasa Indonesia Pada Angkutan Umum Mrt Jakarta Menggunakan Naive Bayes Classifier. Jurnal Ilmiah Informatika Komputer Jilid 25 No. 1.
Taufik, Andi. 2018. Perbandingan Algoritma Text Mining Untuk Klasifikasi Review Hotel. Jurnal Teknik Komputer AMIK BSI, Vol. IV No.2.
Downloads
Published
Issue
Section
License
Copyright (c) 2022 Jurnal JTIK (Jurnal Teknologi Informasi dan Komunikasi)
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.
