Analyzing Public Sentiment toward the Formation of the PrabowoGibran's Kabinet Merah Putih
(1) Universitas Airlangga
(2) Universitas Airlangga
(3) Universitas Airlangga
(*) Corresponding Author
Abstract
This study focuses on analyzing public sentiment towards the Kabinet Merah-Putih formed by Prabowo Subianto and Gibran Rakabuming, based on a survey conducted by Indikator Politik, which indicates that public confidence in the Prabowo-Gibran administration reached 85.3%. Utilizing data sourced from the comment sections of the KompasTV YouTube channel, the analysis employs corpus linguistics, also known as Computer-Mediated Critical Discourse Analysis (CMDA), in conjunction with critical discourse analysis. The methodology selected for this research employs a corpus-based
approach, which facilitates the integration of data selection, collection, and identification in the form of comments reflecting public sentiment regarding the establishment of the Kabinet Merah-Putih, compiled into a Sentiment Cabinet Corpus (Korpus Sentimen Kabinet/ KSK). A total of 70,793 comments were downloaded using web scraping techniques with Octoparse, revealing frequencies and concordances that indicate
both support and opposition.
Keywords
Full Text:
PDFReferences
Alfi, K. Z., & Rosita, F. Y. (2019). Pelanggaran Maksim Kesopanan dalam Kolom Komentar Twitter Joko Widodo. Diglosia: Jurnal Kajian
Bahasa, Sastra, Dan Pengajarannya, 2(2), 73–82.
https://doi.org/10.30872/diglosia.v2i2.19
Annur, C., M. Indonesia Peringkat Keempat Pengguna YouTube Terbanyak di Dunia. Accessed from https://databoks.katadata.co.id/
Fairclough, N. (1995). Media Discourse. London: Edward Arnold Garret (Eds.) Approaches to Media Discourse. Oxford: Blackwell.
Herring, S.C. (2004). Computer-mediated Discouse Analysis: An
Approach to Researching Online Behavior. Designing for Virtual
Communities in the Service of Learning, 338-376.
Hidayat, H. & Saifullah, A., R. (2020). Analisis Tanggapan Pengguna
Youtube Terhadap Pidato Presiden Joko Widodo: Analisis Wacana
Berbasis Korpus. Seminar Internasional Riksa Bahasa. Diakses dari
http://proceedings2.upi.edu/index.php/riksabahasa/article/vie
w/896
Indikator Politik. (2024). Keyakinan dan Ekspektasi Publik terhadap
Pemerintahan Prabowo-Gibran 27 Oktober 2024. https://indikator.co.id/rilis-indikator-27-oktober-2024/
Kusno, A., Arifin, M. B., & Mulawarman, W. G. (2022). Identifikasi Konteks Ekstralingual Virtual Bahasa Media Sosial sebagai Penunjang
Analisis Bahasa sebagai Alat Bukti Hukum. Diglosia: Jurnal Kajian
Bahasa, Sastra, Dan Pengajarannya, 5(1s), 261–282. https://doi.org/10.30872/diglosia.v5i1s.401
Ramadhan, K.. & Eriyanto. (2024). Misinformasi dalam Isu Nikuba:
Analisis Linguistik Korpus Isu Nikuba pada Komentar YouTube.
Jurnal Ilmiah Ilmu Pendidikan, Vol. 7 No. 4.
Salim, I. H., & Suhandano. (2023). The Reporting of Brigadier J Murder on Indonesian Police’s Official News Media: Corpus-Based Discourse Analysis. Journal of Language Intelligence and Culture, 5(1), 55–74. https://jlic.uinkhas.ac.id/index.php/jlic/article/view/120
Sanjaya, G. & Lhaksmana, K.M. (2020). Analisis Sentimen Komentar
YouTube tentang Terpilihnya Menteri Kabinet Indonesia Maju mempergunakan Lexicon Based. E-Proceeding of Engineering, Vol.
(3).
Sekretariat Kabinet Republik Indonesia (2024, Oktober 21). Presiden
Prabowo Subianto Lantik Menteri Kabinet Merah Putih Periode
Tahun 2024-2029. Accessed fromhttps://setkab.go.id/presidenprabowo-subianto-lantik-menteri-kabinet-merah-putih-periodetahun-2024-2029/
SCImago Media Rankings. (2024). Portal Berita Populer 2024 Winter
Edition. https://www.scimagomedia.com/rankings.php?country=Indonesia
Williams, Geoffrey. (2006). Michael Hoey. Lexical Priming: A New Theory of Words and Language. London: Routledge. 2005. xiii+ 202 pages. ISBN 0-415-32863-2. International Journal of Lexicography, 19(3), 327–335.
Zein, D., Wagiati, Darmayanti, N. (2022). Transformasi Makna Leksikal dalam Bahasa Indonesia Mutakhir: Analisis Wacana Termediasi Komputer. Suar Bé tang, 17(2), 247-260. https://www.doi.org/10.26499/surbet.v17i2356
Article Metrics
Abstract view : 0 timesPDF - 0 times
Refbacks
- There are currently no refbacks.
Copyright (c) 2025 English Language and Literature International Conference (ELLiC) Proceedings

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Electronic ISSN: 2579-7263
CD-ROM ISSN: 2579-7549
Published by
FACULTY OF FOREIGN LANGUAGE AND CULTURE
UNIVERSITAS MUHAMMADIYAH SEMARANG
Jl. Kedungmundu Raya No.18 Semarang, Central Java, Indonesia
Phone: +622476740295, email: ellic@unimus.ac.id