AI dalam Pengawasan Maritim Menghadapi Ancaman Hibrida di Asia Tenggara
DOI:
https://doi.org/10.59188/jurnalsosains.v5i11.32572Keywords:
Kecerdasan Buatan, Pengawasan Maritim, Ancaman Hibrida, Keamanan Laut, Asia Tenggara.Abstract
Penelitian ini menelaah peran kecerdasan buatan (AI) dalam meningkatkan efektivitas pengawasan maritim terhadap ancaman hibrida di kawasan Asia Tenggara. Ancaman hibrida, yang menggabungkan dimensi militer, siber, ekonomi, dan informasi, menuntut sistem keamanan laut yang adaptif dan cerdas. Dengan menggunakan pendekatan kualitatif dan analisis literatur strategis, penelitian ini mengidentifikasi bagaimana AI mendukung deteksi dini, analisis data pergerakan kapal, serta penilaian risiko terhadap aktivitas non-konvensional yang mengancam stabilitas kawasan. Hasil penelitian menunjukkan bahwa integrasi AI mampu meningkatkan kemampuan deteksi dan mitigasi ancaman lintas batas melalui otomasi analisis data multi-sumber seperti AIS, radar satelit, dan citra optik. Selain itu, AI berkontribusi dalam memperkuat kerja sama keamanan regional antarnegara ASEAN melalui fusi data dan peningkatan maritime domain awareness. Kendati demikian, tantangan seperti kesenjangan teknologi, isu etika, dan ketergantungan pada sistem asing masih menjadi hambatan utama. Penelitian ini menegaskan bahwa penerapan AI secara kolaboratif dan etis berpotensi menjadi pilar penting dalam membangun arsitektur keamanan laut cerdas dan berkelanjutan di Asia Tenggara.
References
Banerjee, A. (2025, October 8). From Malacca to the Sulu Sea, AI is rewriting maritime security. Modern Diplomacy. Retrieved from https://moderndiplomacy.eu/2025/10/08/from-malacca-to-the-sulu-sea-ai-is-rewriting-maritime-security/
Basuki, A. (2022). Kecerdasan buatan dalam strategi pertahanan maritim Indonesia. Jakarta: Lembaga Kajian Strategis Nusantara.
Bueger, C. (2023). Critical maritime infrastructure protection: What’s the trouble? Marine Policy, 158. https://doi.org/10.1016/j.marpol.2023.105564
Chen, L., Yu, K., & Lee, S. (2022). Artificial intelligence in maritime surveillance: Trends and applications. Ocean Engineering, 254, 111350. https://doi.org/10.1016/j.oceaneng.2022.111350
Creswell, J. W. (2014). Research design: Qualitative, quantitative, and mixed methods approaches (4th ed.). Thousand Oaks, CA: Sage.
Dao, Y., Yusnaldi, Y., & Kusuma, K. (2024). Intelijen Maritim Dalam Penanggulangan Destructive fishing Sebagai Ancaman Keamanan Maritim di Wilayah Pesisir dan Pulau-Pulau Kecil. Jurnal Ilmu Sosial Politik Dan Humaniora.
Fenton, A. (2024). A case study of hybrid maritime security in the Straits. Journal of Ocean and Maritime Studies, 12(3), 510. https://doi.org/10.3390/joms12030510
Guricci, M. F. A., & Seniwati, S. (2024). Strategi Keamanan Maritim di Asia Tenggara: Kerjasama Diplomasi maritim di ASEAN. КОНСЕНСУС.
Koh, D. (2022). Hybrid maritime threats in the Indo-Pacific: Emerging trends and responses. Pacific Review, 35(4), 675–694. https://doi.org/10.1080/09512748.2022.2056668
Nguyen, H. T. (2024). Ethical challenges in AI-based maritime security systems. Asian Journal of Maritime Affairs, 16(2), 145–167.
Patton, M. Q. (2015). Qualitative research & evaluation methods (4th ed.). Thousand Oaks, CA: Sage.
Rahim, M. (2021). Maritime domain awareness in Southeast Asia: Challenges and prospects. Defence and Security Analysis, 37(3), 267–284.
Rahman, M., & Hashim, R. (2023). AI-driven maritime governance and security in ASEAN waters. Maritime Policy & Management, 50(6), 812–829.
Santos, J. M. (2023). ASEAN maritime cooperation and the role of emerging technologies. Asian Security Review, 19(1), 55–78.
Talpur, K. (2025). AI in maritime security: Applications, challenges, future directions. Information, 16(8), 658. https://doi.org/10.3390/info160800658
Tan, E. (2023). AI governance frameworks and regional security integration: Lessons from Singapore. Journal of Cyber Policy, 8(2), 220–243.
Tanaka, T. (2023). Japan’s strategic AI partnerships with Southeast Asia. Asia-Pacific Policy Studies, 10(1), 45–63.
Thomas, G., & Lim, C. (2024). Reinforcement learning in maritime safety operations. IEEE Transactions on Intelligent Transportation Systems, 25(7), 9120–9134.
Wijaya, R. (2023). Deep learning approaches for detecting illegal vessels in Indonesian waters. Indonesian Journal of Marine Technology, 4(2), 123–141.
Windward. (2025, April 27). How AI is transforming maritime security in APAC. Windward Insights. Retrieved from https://windward.ai/knowledge-base/how-ai-is-transforming-maritime-security-in-apac/
Zhang, Q., Liu, F., & Zhao, H. (2021). Satellite-based deep learning for maritime dark target detection. Remote Sensing Letters, 12(9), 876–889. https://doi.org/10.1080/2150704X.2021.1948715
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Copyright (c) 2025 Rudiyanto Rudiyanto, Yusnaldy Yusnaldy, Bayu Asih Yulianto, Lukman Yudho Prakoso, Muhammad Risahdi
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