Sentiment Analysis to Know Public Perception Regarding to Public Communication of Indonesian Customs and Excise

Authors

  • Baskoro Tri Nugroho Universitas Informatika dan Bisnis Indonesia
  • Achwan Noorlistyo Adi Universitas Informatika dan Bisnis Indonesia

DOI:

https://doi.org/10.61194/ijcs.v2i1.222

Keywords:

Bea Cukai, Social Media Analytics, Sentiment Analytics, Customs Agency

Abstract

This study highlights the positive impact of social media sentiment analysis in enhancing public perception of the Directorate General of Customs and Excise in Indonesia. By employing the Social Media Analytics (SMA) framework and the Brand24 tool, the research examines public sentiment on Twitter and TikTok during two periods in 2024. The findings reveal a significant improvement in sentiment from May to mid-August, driven by the government's proactive and transparent communication, including direct intervention by the Minister of Finance. This shift underscores the effectiveness of responsive governance in fostering public trust and engagement. The study emphasizes the value of ongoing sentiment monitoring, proactive communication strategies, and the promotion of ethical standards as key to maintaining and further enhancing public confidence. These insights contribute positively to the understanding of social media’s role in public sector communication and its potential to support better governance.

References

Arts, K., Ioris, A. A. R., Macleod, C. J. A., Han, X., Sripada, S. G., Braga, J. R. Z., & van der Wal, R. (2016). Environmental communication in the Information Age: Institutional barriers and opportunities in the provision of river data to the general public. Environmental Science and Policy, 55, 47–53. https://doi.org/10.1016/j.envsci.2015.08.011

Cahyono, Y. (2017). Analisis Sentiment pada Sosial Media Twitter Menggunakan Naїve Bayes Classifier dengan Feature Selection Particle Swarm Optimization dan Term Frequency. Jurnal Informatika Universitas Pamulang, 2(1), 14. https://doi.org/10.32493/informatika.v2i1.1500

CNN Indonesia. (2024). Bea Cukai Ramai “Dirujak” Netizen, di mana Letak Masalahnya? . In https://www.cnnindonesia.com/ekonomi/20240430065307-532-1092001/bea-cukai-ramai-dirujak-netizen-di-mana-letak-masalahnya.

de las Heras-Pedrosa, C., Jambrino-Maldonado, C., Rando-Cueto, D., & Iglesias-Sánchez, P. P. (2022). COVID-19 Study on Scientific Articles in Health Communication: A Science Mapping Analysis in Web of Science. International Journal of Environmental Research and Public Health, 19(3). https://doi.org/10.3390/ijerph19031705

Dwianto, R. A., Nurmandi, A., & Salahudin, S. (2021). The Sentiments Analysis of Donald Trump and Jokowi’s Twitters on Covid-19 Policy Dissemination. Webology, 18(1), 389–405. https://doi.org/10.14704/WEB/V18I1/WEB18096

Gautam, G., & Yadav, D. (2014). Sentiment analysis of twitter data using machine learning approaches and semantic analysis. 2014 Seventh International Conference on Contemporary Computing (IC3), 437–442. https://doi.org/10.1109/IC3.2014.6897213

Hansen, S. L., & Hilbrich, I. (2022). Exclusion, Engagement, and Empathy: Revisiting Public Discourse from a Communication Perspective. Social Epistemology, 36(1), 1–8. https://doi.org/10.1080/02691728.2021.2004622

Hartgerink, C. H. J., & van Zelst, M. (2018). “As-you-go” instead of “after-the-fact”: A network approach to scholarly communication and evaluation. Publications, 6(2). https://doi.org/10.3390/publications6020021

Holsapple, C. W., Hsiao, S.-H., & Pakath, R. (2018). Business social media analytics: Characterization and conceptual framework. Decision Support Systems, 110, 32–45. https://doi.org/10.1016/j.dss.2018.03.004

Hong, N. (2022). Digital-Media-Based Interaction and Dissemination of Traditional Culture Integrating Using Social Media Data Analytics. Computational Intelligence and Neuroscience, 2022. https://doi.org/10.1155/2022/5846451

Hutagalung, S. S., Kartika, T., & Suciska, W. (2023). Media Monitoring Analysis of Government Image in Infrastructure Development in Indonesia. Jurnal Komunikasi, 15(1), 212–227. https://doi.org/10.24912/jk.v15i1.20605

Ibrahim, C., Jaya, A., Simatupangᶟ, Y., Daado, J., Azizah, N., Fachriyyatul Ismah, mal, & Ansar, F. (2021). THE SENTIMENT ANALYSIS OF INDONESIAN NATIONAL LIBRARY’S TWITTER AND INSTAGRAM. 5(2), 48. https://www.perpusnas.go.id/task_function_we

Jia, H. (2022). More engagement but less participation: China’s alternative approach to public communication of science and technology. Public Understanding of Science, 31(3), 331–339. https://doi.org/10.1177/09636625221090729

Lemon, L. L., & VanDyke, M. S. (2021). Expanding the discussion on internal management of risk communication: A critique of the current risk communication literature. Public Relations Inquiry, 10(3), 377–394. https://doi.org/10.1177/2046147X211014086

Moore, K. R. (2016a). Public Engagement in Environmental Impact Studies: A Case Study of Professional Communication in Transportation Planning. IEEE Transactions on Professional Communication, 59(3), 245–260. https://doi.org/10.1109/TPC.2016.2583278

Moore, K. R. (2016b). Public Engagement in Environmental Impact Studies: A Case Study of Professional Communication in Transportation Planning. IEEE Transactions on Professional Communication, 59(3), 245–260. https://doi.org/10.1109/TPC.2016.2583278

Moss, G., Kennedy, H., Moshonas, S., & Birchall, C. (2015). Knowing your publics: The use of social media analytics in local government. Information Polity, 20(4), 287–298. https://doi.org/10.3233/IP-150376

Murfi, H., Siagian, F. L., & Satria, Y. (2019). Topic features for machine learning-based sentiment analysis in Indonesian tweets. International Journal of Intelligent Computing and Cybernetics, 12(1), 70–81. https://doi.org/10.1108/IJICC-04-2018-0057

Nulty, P., Theocharis, Y., Popa, S. A., Parnet, O., & Benoit, K. (2016). Social media and political communication in the 2014 elections to the European Parliament. Electoral Studies, 44, 429–444. https://doi.org/10.1016/j.electstud.2016.04.014

Patel, V. R., Gereta, S., Jafri, F., Mackert, M., & Haynes, A. B. (2023). Examining Public Communication About Surgical Cancer Care on Twitter. Journal of Surgical Research, 291, 433–441. https://doi.org/10.1016/j.jss.2023.06.048

Pratama, Y., Roberto Tampubolon, A., Diantri Sianturi, L., Diana Manalu, R., & Frietz Pangaribuan, D. (2019). Implementation of Sentiment Analysis on Twitter Using Naïve Bayes Algorithm to Know the People Responses to Debate of DKI Jakarta Governor Election. Journal of Physics: Conference Series, 1175, 012102. https://doi.org/10.1088/1742-6596/1175/1/012102

Prayoga, K. (2020). How Jokowi Communicates with the Public During Covid-19 Crisis: An Analysis of Tweets on Twitter. Jurnal Komunikasi: Malaysian Journal of Communication, 36(2), 434–456. https://doi.org/10.17576/JKMJC-2020-3602-26

Reddick, C. G., Chatfield, A. T., & Ojo, A. (2017). A social media text analytics framework for double-loop learning for citizen-centric public services: A case study of a local government Facebook use. Government Information Quarterly, 34(1), 110–125. https://doi.org/10.1016/j.giq.2016.11.001

Stieglitz, S., Mirbabaie, M., Ross, B., & Neuberger, C. (2018). Social media analytics – Challenges in topic discovery, data collection, and data preparation. International Journal of Information Management, 39, 156–168. https://doi.org/10.1016/j.ijinfomgt.2017.12.002

Suseno, Y., Laurell, C., & Sick, N. (2018). Assessing value creation in digital innovation ecosystems: A Social Media Analytics approach. Journal of Strategic Information Systems, 27(4), 335–349. https://doi.org/10.1016/j.jsis.2018.09.004

Tsou, M.-H., Jung, C.-T., Allen, C., Yang, J.-A., Gawron, J.-M., Spitzberg, B. H., & Han, S. (2015). Social media analytics and research test-bed (SMART dashboard). Proceedings of the 2015 International Conference on Social Media & Society, 1–7. https://doi.org/10.1145/2789187.2789196

Wang, X., Wong, Y. D., Li, K. X., & Yuen, K. F. (2021). Shipping industry’s sustainability communications to public in social media: A longitudinal analysis. Transport Policy, 110, 123–134. https://doi.org/10.1016/j.tranpol.2021.05.031

We Are Social. (2024). DIGITAL 2024 INDONESIA.

Yang, Z. (2021). Deconstruction of the discourse authority of scientists in Chinese online science communication: Investigation of citizen science communicators on Chinese knowledge sharing networks. Public Understanding of Science, 30(8), 993–1007. https://doi.org/10.1177/09636625211005106

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Published

2024-02-27

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