REPRESENTASI IDEOLOGI DAN PESAN SOSIAL: STUDI MULTIMODAL PADA TAYANGAN VIDEO ANOMALI AI
Abstract
Abstrak
Penelitian ini menganalisis representasi ideologi dan pesan sosial dalam tayangan video berbasis kecerdasan buatan (AI) Skibidi Toilet dan Anomali AI Tung-Tung Sahur melalui pendekatan Critical Multimodal Discourse Analysis (CMDA). Data diperoleh dari cuplikan video berdurasi pendek, transkrip multimodal, dan komentar penonton yang diambil dari YouTube dan TikTok pada periode Juni–Oktober 2025. Hasil penelitian menunjukkan bahwa kedua tayangan mengandalkan estetika absurd-surreal yang berfungsi sebagai “mesin memetisasi” (memetic engine) yang mendorong viralitas melalui repetisi audio, visual grotesque, dan narasi modular yang mudah diremix. Analisis mengungkap tiga representasi ideologis utama: (1) ideologi teknologisasi dan dehumanisasi, ditandai oleh figur camera-head, toilet-head, dan wajah generatif-AI yang menegaskan kaburnya batas manusia-mesin; (2) ideologi komodifikasi budaya, terutama pada Tung-Tung Sahur yang merekonstruksi ritual sahur menjadi komoditas viral dalam ekosistem ekonomi perhatian; dan (3) ideologi absurdity sebagai strategi kapitalisme digital, keanehan visual dan ritme audio digunakan sebagai alat retensi dan monetisasi. Makna sosial terbentuk pada tiga level: mikro (pengalaman afektif individu yang ambivalen––antara hiburan dan ketidaknyamanan), meso (dinamika komunitas online melalui praktik remix dan negosiasi identitas generasional), dan makro (peran algoritma dalam mengonstruksi estetika viral dan budaya digital global). Temuan ini menegaskan bahwa konten absurd-AI bukan sekadar hiburan, melainkan arena produksi makna yang memperlihatkan relasi kuasa antara teknologi, budaya lokal, dan ekonomi platform digital. Penelitian ini berkontribusi pada pengembangan kajian multimodal serta mendorong literasi kritis masyarakat terhadap media digital kontemporer.
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Abdalla, M., Javed, S., Radi, M. A. L., & Ulhaq, A. (2024). Video Anomaly Detection in 10 Years : A Survey and Outlook. Video Anomaly Detection in 10 Years: A Survey and Outlook. Neural Computing and Applications., 4(1), 1–16.
Adeagbo, E. O., & Kabir, A. (2024). Visualising Ideological Dichotomies in Nigerian Presidential. Journal of African Studies and Sustainable Development, 7(5), 45–60.
Al-ahmad, S., & Nawasreh, A. (2024). Discourse Analysis of ISIS Ideology Show Cased in Speeches addressing. 16(1), 23–40.
Aluya, I., & Iangba, T. (2024). A Multimodal Discourse Study of Visual Images in Select Online News Discourse on the 2023 General Elections in Nigeria. Canadian Journal of Language and Literature Studies, 4(1), 6–26. https://doi.org/10.53103/cjlls.v4i1.144
Biria, R., & Boshrabadi, A. M. (2016). The Efficacy of Multimodal Vs . Print-Based Texts for Teaching Reading Comprehension Skills to. International Journal of Language and Applied Lingusitic World, January 2014.
Bryson, J. J. (2019). The past decade and future of AI ’ s Impact on Society 1. 11.
Cervi, L., & Divon, T. (2023). Playful Activism : Memetic Performances of Palestinian Resistance in TikTok # Challenges. Social Media Society, 1(13), 1–13. https://doi.org/10.1177/20563051231157607
Cohen, P. R., Technologies, V., Johnston, M., Mcgee, D., & Oviatt, S. L. (2014). The Efficiency Of Multimodal Interaction : A Case Study. ResearchGate, 1(3), 1–32.
Creswell. (2018). Research Desain Qualitative, Quantitatif, Mixed Methods Approaches (5th ed.). London (United Kingdom): SAGE Publications, Inc.
Danaher, B. J., & Galway, N. U. I. (2014). The Rise of the Robots and the Crisis of Moral Patiency. Pre-Publication Version of AI Dan Society, 1(1), 1–18. https://doi.org/10.1007/s00146-017-0773-9
Dionis-ros, A., Vila-francés, J., Serrano-lópez, A. J., Magdalena-benedito, R., & Mateo, F. (2024). Multimodal Video Analysis for Crowd Anomaly Detection Using Open Access Tourism Cameras. MDPI Journal Applied Siences, 14(11075), 2–15.
Fairclough, N. (2012). Critical Discourse Analysis. 7(July), 452–487.
Fairclough, N. (2018). Critical Discourse Analysis.
Firmansyah, B. M. (2018). Multimodal conception in learning. ISLLAC : Journal of Intensive Studies on Language, Literature, Art, and Culture Volume, 2(1), 40–44. https://doi.org/10.17977/um006v2i12018p040
Habib, H., & Hussain, M. S. (2024). A Socio-Semiotic Study of Media Gender Misrepresentation Impact on Youth’s Cognition and Ideology. Journal of Sosial Sciences Development, 3(2), 299–312.
Holsanova, J. &. (2012). New Methods for Studying Visual Communication and Multimodal Integration. Visual Communication, 11(3), 251–257. https://doi.org/10.1177/1470412912446558
Jewitt, C., & Jones, R. H. (2009). The Routledge Handbook of Multimodal Analisis (pp. 114–126). Routledge, Tylor & Francis Group; London and New York.
Kang, S., Kim, D., & Kim, Y. (2019). A visual-physiology multimodal system for detecting outlier behavior of participants in a reality TV show. International Journal of Distrubted Sensor Networks, 15(7), 1–26. https://doi.org/10.1177/1550147719864886
Livingstone, S. (2014). The participation paradigm in audience research. Londen School of Economics and Political Scinece (LSE). https://doi.org/10.1080/10714421.2013.757174
Lupton, D. (2016). You are Your Data: Self-tracking Practices and Concepts of Data (pp. 1–18). Springer International Publishing.
Lv, H., & Sun, Q. (2024). Video Anomaly Detection and Explanation via Large Language Models. ArXiv Preprint ArXiv:2401.05702., 1(1), 1–24.
Nguyen, T. A. M. V, Nguyen, K., Tran, T. M., Vu, T. U. N., & Vo, N. D. (2022). Anomaly Analysis in Images and Videos : A Comprehensive Review. 55(7).
Nouri, J. (2019). Students Multimodal Literacy and Design of Learning During Self ‑ Studies in Higher Education. Technology, Knowledge and Learning, 24(4), 683–698. https://doi.org/10.1007/s10758-018-9360-5
O’Halloran, K. L. (2021). Multimodal Discourse Analysis. 249–266.
Pontoh, S. (2024). Ideology Construction of Digital News Media Related to the Vortex Discourse of the 2024 Election. Al-Lisan: Jurnal Bahasa, 9(2), 99–121.
Qi, Y. (2017). Propaganda in focus: decoding the media strategy of ISIS. Humanities and Social Sciences Communications, 2024, 1–12. https://doi.org/10.1057/s41599-024-03608-y
Rahardi, R. K. (2024). Peran Konteks Siberteks Multimodal Visual di Ruang Publik Maya. Linguistik Indonesia, 42(1), 127–140.
Rehman, A., Ullah, H. S., Farooq, H., Owais, H., & Khan, A. (2021). Multi-Modal Anomaly Detection by Using Audio and Visual Cues. IEEE Access, 9(1), 30587–30603. https://doi.org/10.1109/ACCESS.2021.3059519
Ruiz-madrid, N., & Valeiras-jurado, J. (2020). Developing multimodal communicative competence in emerging academic and professional genres. Internatiional Journal of ENglish Studies, 20(1), 27–50. https://doi.org/10.6018/ijes.401481
Setyo, A. A., Pomalato, S. W., Hulukati, E. P., Machmud, T., & Djafri, N. (2023). Effectiveness of TPACK-Based Multimodal Digital Teaching Materials for Mathematical Critical Thinking Ability. International Journal of Information and Education, 13(10), 1604–1608. https://doi.org/10.18178/ijiet.2023.13.10.1968
Shika, S. M. (2024). Lexical Choces and Indeology in Nigeria’s Scurity and Development Discourse in Nigeria’S Media. ESTAGA: Journal of Enhglish Language and Literary, 1(1), 65–90.
Skiba, R. (2024). Examining the Ideological Foundations , Psychological Influences, and Media Representation of Extremism and Its Social Impact. Advances in Applied Sociology, 14, 469–503. https://doi.org/10.4236/aasoci.2024.149033
Supatmiwati, D., Hastuti, H., Fissilmi, A., & Putri, T. R. (2025). Ideology and Communication Strategy of Indonesia ’ s 2024 Presidential Candidates : A Transitivity Analysis. HUmanistis: Journal of Language and Literature, 11(2), 175–190. https://doi.org/10.30812/humanitatis.v11i2.4996
Tran, K. act. (2025). Delivering News In 60 Seconds : U . S . News Publishers ’ Motivations And Practices on TIKTOK presented to the Faculty of the Graduate School at the University of Missouri-Columbia In Partial Fulfillment of the Requirements for the Degree Master of Arts K. In University of Missouri-Columbia (Issue May 2025, pp. 1–154).
Wang, H. (2022). International English Learners ’ Perspectives on Multimodal Composing and Identity Representation Via Multimodal Texts. SAGE Open, 1(5), 1–15. https://doi.org/10.1177/21582440221103526
Wang, Y., Zhao, Y., Huo, Y., & Lu, Y. (2025). Multimodal anomaly detection in complex environments using video and audio fusion. 1–22.
Wiggins, B. E., & Bowers, G. B. (2014). Memes as genre: A structurational analysis of the memescape. New Media Society Pusblished (SAGE), 17(11), 1886-1906. https://doi.org/10.1177/1461444814535194
Zulli, D., & Zulli, D. J. (2020). Extending the Internet meme : Conceptualizing technological mimesis and imitation publics on the TikTok platform. https://doi.org/10.1177/1461444820983603
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