Analysis of Indonesian Netizen Sentiment Towards the Government's Campaign on the Use of Artificial Intelligence Using the Naive Bayes Algorithm

Authors

  • Salsabila Nasution Universitas Islam Negeri Sumatera Utara Author
  • Asro Hayati Berutu Universitas Islam Negeri Sumatera Utara Author
  • Fatwa Aulia Universitas Islam Negeri Sumatera Utara Author

DOI:

https://doi.org/10.64803/cessmuds.v1.28
   

Keywords:

Artificial Intelligence, Netizen Sentiment, Naive Bayes, Social Media, Sentiment Analysis

Abstract

The development of artificial intelligence (AI) has encouraged the Indonesian government to adopt this technology in various public service sectors. However, the use of AI has received mixed responses from the public, particularly on social media. This study aims to analyze Indonesian netizen sentiment towards the government's AI campaign using the Naive Bayes algorithm. Data was collected from the Twitter platform and analyzed through preprocessing, sentiment classification, and model evaluation. The results show that the majority of netizen sentiment is negative, with concerns related to unfairness for creative workers, a lack of regulation, and the use of AI for political gain. This research is expected to provide input for the government in designing more ethical and inclusive AI adoption policies.

References

Brojonegoro, B. P. S., & Riza, H. (2020). INDONESIA’S NATIONAL ARTIFICIAL INTELLIGENCE STRATEGY 2020-2045. BPS.

Darwis, D., Siskawati, N., & Abidin, Z. (2021). Application of Naive Bayes Algorithm for Sentiment Analysis of National BMKG Twitter Data Review. Jurnal TEKNO KOMPAK, 15(1).

Kumar, S., & Garg, N. (2021). Sentiment Analysis of Twitter Data Using Machine Learning Algorithms: A Review. Journal of Computer Science and Applications, 9(3), 45–52. https://doi.org/10.11648/j.jcsa.20210903.12

Munsyi, M. A., Nareswari, K. P., & Dewiyanti, S. (2023). Application of AI in improving local government information systems at DPMPTSP Nganjuk Regency. Proceeding of National Conference on Accounting & Finance, 5, 36–44. https://doi.org/10.20885/ncaf.vol5.art4

Nurmalasari, S., Hidayanto, A. N., Huwaida, L. A., & Wulandari, H. (2023). Sentiment Analysis and Topic Modeling of Citizen Satisfaction with the Indonesian Government in Handling a Pandemic. American Journal of Open Research, 2(7), 1–7. https://www.researchgate.net/publication/373379405

Putri, D. D., Nama, G. F., & Sulistiono, W. E. (2022). Sentiment Analysis of the House of Representatives (DPR) Performance on Twitter Using the Naive Bayes Classifier Method. Journal of Informatics and Applied Electrical Engineering, 10(1), 34–40. https://doi.org/10.23960/jitet.v10i1.2262

Rahmawati, D., & Santoso, A. (2022). Implementation of Naive Bayes Algorithm for Sentiment Analysis on Public Opinion about Government Policy in Indonesia. Jurnal Teknologi Dan Sistem Komputer, 10(2), 85–92. https://doi.org/10.14710/jtsiskom.2022.10285

Sasongko, N. (2020). STRATEGI NASIONAL KECERDASAN ARTIFISIAL INDONESIA Strategi Nasional Kecerdasan Artifisial adalah arah kebijakan nasional yang memuat area fokus dan bidang prioritas teknologi kecerdasan artifisial yang sebagai acuan kementerian, lembaga, pemerintah daerah dan pemangku kepentingan lainnya dalam melaksanakan kegiatan di bidang teknologi kecerdasan artifisial di Indonesia. TAHUN 2020-2045.

Wijaya, R., & Nugroho, Y. (2023). Exploring Public Perception of Artificial Intelligence in Indonesia through Social Media Analysis. International Journal of Artificial Intelligence Research, 7(1), 1–10. https://doi.org/10.29099/ijair.v7i1.451

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Published

2025-11-01

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Section

Articles

How to Cite

Analysis of Indonesian Netizen Sentiment Towards the Government’s Campaign on the Use of Artificial Intelligence Using the Naive Bayes Algorithm. (2025). Proceedings of The International Conference on Computer Science, Engineering, Social Science, and Multi-Disciplinary Studies, 1, 208-212. https://doi.org/10.64803/cessmuds.v1.28