Media Sosial Sebagai Arena Komunikasi Bencana

Analisis Sentimen Publik atas Banjir Jabodetabek

Authors

  • Windhiadi Yoga Sembada Universitas Pembangunan Nasional Veteran Jakarta

Keywords:

Banjir Jabodetabek, Analisis Sentimen, Mixed Method, Crisis Communications

Abstract

This research aims to understand how the public responds to the Greater Jakarta flood in January 2026 through social media. The main question asked is how the dynamics of public sentiment will be formed during January 2026 on social media. This study uses mixed methods, combining quantitative analysis of sentiment on social media with qualitative interpretation of public narratives. This analysis is confronted with crisis communication theory, media framing and agenda setting to explain the narrative from informative to political. The results of this study show that during the social media conversation narrative period in January 2026 there were 2 peak conversations, namely January 12 and 24 which showed a shift in conversation patterns that were previously in the form of complaints, netizens' surprise became dominated by socio-political conversations and even indicated imagery with the dominance of certain actors as the main amplifier. The results of this study remind that the effectiveness of disaster communication that occurs is not only on the issue of speed, transparency, and the ability to maintain public trust. The next recommendation is to expand the analysis of public discourse in a qualitative manner, compare flood cases with other disasters in Indonesia, and examine the role of the media and political actors in strengthening or weakening public trust. These findings are expected to be the basis for a more adaptive, participatory, and restore-oriented disaster communication strategy.

References

Azhar, M. S. (2026, January 24). Banjir Jakarta, 90 RT dan 9 Ruas Jalan Tergenang pada Sabtu. Metro TV News. https://www.metrotvnews.com/read/bzGCe9lV-banjir-jakarta-90-rt-dan-9-ruas-jalan-tergenang-pada-sabtu

Choirul Rahmadan, M., Nizar Hidayanto, A., Swadani Ekasari, D., Purwandari, B., & Theresiawati. (2020). Sentiment Analysis and Topic Modelling Using the LDA Method related to the Flood Disaster in Jakarta on Twitter. 2020 International Conference on Informatics, Multimedia, Cyber and Information System (ICIMCIS), 126–130. https://doi.org/10.1109/ICIMCIS51567.2020.9354320

Elfattah, H. Y. A. (2024). Social Media and Crisis Communication: A Narrative Literature Review of Public Engagement and Policy Implications. Sinergi International Journal of Communication Sciences, 2(3), 167–179. https://doi.org/10.61194/ijcs.v2i3.650

Elmada, M. A. G., Stephani, N., & Ariestya, A. (2023). Making The Disaster Trending. Jurnal Kajian Media, 7(1), 27–37. https://doi.org/10.25139/jkm.v7i1.5295

Hafiez, F. A. (2026, January 12). Banjir Jakarta Meluas, 23 Ruas Jalan dan 10 RT Tergenang. Mettro TV News. https://www.metrotvnews.com/read/NQAC0Vgw-banjir-jakarta-meluas-23-ruas-jalan-dan-10-rt-tergenang

Han, X., & Wang, J. (2019). Using Social Media to Mine and Analyze Public Sentiment during a Disaster: A Case Study of the 2018 Shouguang City Flood in China. ISPRS International Journal of Geo-Information, 8(4), 185. https://doi.org/10.3390/ijgi8040185

Kartikawati, D., Dian Metha Ariyanti, & Purnomo. (2025). CORPORATE CRISIS COMMUNICATION IN THE AGE OF SOCIAL MEDIA: A LITERATURE REVIEW ON STRATEGIC ADAPTATION AND PUBLIC ENGAGEMENT. Indonesian Journal of Social Science and Education (IJOSSE), 1(3), 78–89. https://doi.org/10.62567/ijosse.v1i3.1016

Li, W., Haunert, J., Knechtel, J., Zhu, J., Zhu, Q., & Dehbi, Y. (2023a). Social media insights on public perception and sentiment during and after disasters: The European floods in 2021 as a case study. Transactions in GIS, 27(6), 1766–1793. https://doi.org/10.1111/tgis.13097

Li, W., Haunert, J., Knechtel, J., Zhu, J., Zhu, Q., & Dehbi, Y. (2023b). Social media insights on public perception and sentiment during and after disasters: The European floods in 2021 as a case study. Transactions in GIS, 27(6), 1766–1793. https://doi.org/10.1111/tgis.13097

Mustofa, M. U., Aulia, M. R., Ramadhani, R., & Nurfadillah, K. S. (2022). The Flood Politicization and Social Media: Ecological Disaster, Satire, and the Contestation of the 2024 Indonesia Presidential Election on Twitter. JISPO Jurnal Ilmu Sosial Dan Ilmu Politik, 12(1), 39–62. https://doi.org/10.15575/jispo.v12i1.14577

Pratama, H. Y., & Mustofa, M. U. (2025). Narasi Selat Muria dalam Membentuk Persepsi Publik atas Banjir Besar Demak Maret 2024: Sebuah Analisis Wacana Kritis. Journal of Political Issues, 7(1), 17–33. https://doi.org/10.33019/jpi.v7i1.282

Qiu, Y., & Han, H. (2025). A Clustering Study of Online Public Opinion Texts on Public Emergency Events Based on Sentence-Level Similarity and Sentiment Analysis. Applied Mathematics and Nonlinear Sciences, 10(1). https://doi.org/10.2478/amns-2025-1018

Saddam, M. A., Dewantara, E. K., & Solichin, A. (2023). Sentiment Analysis of Flood Disaster Management in Jakarta on Twitter Using Support Vector Machines. Sinkron, 8(1), 470–479. https://doi.org/10.33395/sinkron.v8i1.12063

Soomro, S., Boota, M. W., Zwain, H. M., Soomro, G.-Z., Shi, X., Guo, J., Li, Y., Tayyab, M., Aamir Soomro, M. H. A., Hu, C., Liu, C., Wang, Y., Wahid, J. A., Bai, Y., Nazli, S., & Yu, J. (2024). How effective is twitter (X) social media data for urban flood management? Journal of Hydrology, 634, 131129. https://doi.org/10.1016/j.jhydrol.2024.131129

Tariq, F., Tufail, M., & Rehman, T. (2025). Analyzing the impact of social media sentiments on government response during natural disasters in Pakistan. Big Data and Computing Visions, 5(1), 11–23. https://doi.org/10.22105/bdcv.2024.488065.1217

Wang, W., Zhu, X., Lu, P., Zhao, Y., Chen, Y., & Zhang, S. (2024). Spatio-temporal evolution of public opinion on urban flooding: Case study of the 7.20 Henan extreme flood event. International Journal of Disaster Risk Reduction, 100, 104175. https://doi.org/10.1016/j.ijdrr.2023.104175

Downloads

Published

2026-02-19