Artificial Intelligence and Maritime Governance: Policy Challenges in Combating Illegal Fishing in the Natuna Exclusive Economic Zone
Keywords:
Artificial Intelligence, Maritime Governance, Illegal Fishing, Natuna Exclusive Economic Zone, Policy Challenges, Maritime Security, Sustainability.
Abstract
The Natuna Exclusive Economic Zone (EEZ) is one of Indonesia’s most strategic maritime areas, facing persistent threats from illegal, unreported, and unregulated (IUU) fishing that undermine national sovereignty, food security, and marine sustainability. Conventional maritime patrols have proven inadequate due to limited resources, adverse weather, and the vastness of the region. This study explores the role of artificial intelligence (AI) in strengthening maritime governance, with particular attention to policy challenges in addressing IUU fishing in the Natuna EEZ. Using a qualitative-analytical case study approach, the research identifies major issues such as inter-agency coordination, legal recognition of digital evidence, and community participation in surveillance efforts. The findings show that AI can enhance maritime monitoring through multisensor data integration, trajectory prediction, and anomaly detection in vessel movements. However, the effectiveness of AI systems depends on institutional interoperability, legal adaptation, and inclusive governance mechanisms. The study concludes that AI integration in maritime governance represents a multidimensional reform rather than a purely technical advancement. It bridges technology, law, and environmental management, positioning AI as a strategic instrument to safeguard Indonesia’s maritime sovereignty and strengthen its contribution to Indo-Pacific security cooperation.
References
Brennan, J., & Germond, B. (2024). A methodology for analyzing the impacts of climate change on maritime security. Climatic Change, 177, Article 15. https://doi.org/10.1007/s10584-023-03676-0
Burmeister, H.-C., & Constapel, M. (2021). Autonomous collision avoidance at sea: A survey. Frontiers in Robotics and AI, 8, 739013. https://doi.org/10.3389/frobt.2021.739013
Chen, X., Xu, Q., & Li, L. (2023). Illegal, unreported, and unregulated fishing governance in disputed maritime areas: Reflections on the international legal obligations of states. Fishes, 8(1), 36. https://doi.org/10.3390/fishes8010036
Choi, E. C. (2023). Investigating the management of marine sand mining: A case of West Sea Exclusive Economic Zone in South Korea. Regional Studies in Marine Science, 66, 103109. https://doi.org/10.1016/j.rsma.2023.103109
Coventry, T. (2023). Seizing stateless smuggling vessels on the Mediterranean High Seas. Leiden Journal of International Law, 36(4), 925–946. https://doi.org/10.1017/S092215652300016X
Escalle, L., Mourot, J., Hamer, P., Hare, S. R., Phillip Jr., N. B., & Pilling, G. M. (2023). Towards non-entangling and biodegradable drifting fish aggregating devices – Baselines and transition in the world's largest tuna purse seine fishery. Marine Policy, 149, 105500. https://doi.org/10.1016/j.marpol.2023.105500
Fang, B., Yu, J., Chen, Z., Osman, A. I., Farghali, M., Ihara, I., Hamza, E. H., Rooney, D. W., & Yap, P.-S. (2023). Artificial intelligence for waste management in smart cities: A review. Environmental Chemistry Letters, 21, 1959–1989. https://doi.org/10.1007/s10311-023-01604-3
Goodman, A. J., Walker, T. R., Brown, C. J., Wilson, B. R., Gazzola, V., & Sameoto, J. A. (2020). Benthic marine debris in the Bay of Fundy, eastern Canada: Spatial distribution and categorization using seafloor video footage. Marine Pollution Bulletin, 150, 110722. https://doi.org/10.1016/j.marpolbul.2019.110722
Grønsund, T., & Aanestad, M. (2020). Augmenting the algorithm: Emerging human-in-the-loop work configurations. Journal of Strategic Information Systems, 29(3), 101614. https://doi.org/10.1016/j.jsis.2020.101614
Harris, J. L., Collins, C., Spalding, M., & Stevens, G. M. W. (2024). First records of the sicklefin (Mobula tarapacana), bentfin (Mobula thurstoni), and spinetail (Mobula mobular) devil rays in the Chagos Archipelago. Journal of Fish Biology, 104(6), 1628–1632. https://doi.org/10.1111/jfb.15678
He, Z., Wang, C., Gao, J., & Xie, Y. (2023). Assessment of global shipping risk caused by maritime piracy. Heliyon, 9, e20988. https://doi.org/10.1016/j.heliyon.2023.e20988
Ichimura, Y., Dalaklis, D., Kitada, M., & Christodoulou, A. (2022). Shipping in the era of digitalization: Mapping the future strategic plans of major maritime commercial actors. Digital Business, 2, 100022. https://doi.org/10.1016/j.digbus.2022.100022
Jang, J.-G., Noh, C.-M., Kim, S.-S., Shin, S.-C., Lee, S.-S., & Lee, J.-C. (2022). Vibration data feature extraction and deep learning-based preprocessing method for highly accurate motor fault diagnosis. Journal of Computational Design and Engineering, 10(1), 204–220. https://doi.org/10.1093/jcde/qwac128
Khobragade, J. W., Kumar, A., Abd Aziz, S. N. B., & Maurya, D. (2021). The anti-maritime piracy law in India and Malaysia: An analytical study. Journal of International Maritime Safety, Environmental Affairs, and Shipping, 5(4), 208–219. https://doi.org/10.1080/25725084.2021.2006462
Liu, X. (2022). The supervision and multi-sectoral guarantee mechanism of the global marine sulfur limit—Assessment from Chinese shipping industry. Frontiers in Marine Science, 9, 1028388. https://doi.org/10.3389/fmars.2022.1028388
Moreno, G., Salvador, J., Zudaire, I., Murua, J., Pelegrí, J. L., Uranga, J., Murua, H., Grande, M., Santiago, J., & Restrepo, V. (2023). The Jelly-FAD: A paradigm shift in the design of biodegradable fish aggregating devices. Marine Policy, 147, 105352. https://doi.org/10.1016/j.marpol.2022.105352
Munim, Z. H., Dushenko, M., Jimenez, V. J., Shakil, M. H., & Imset, M. (2020). Big data and artificial intelligence in the maritime industry: A bibliometric review and future research directions. Maritime Policy & Management, 47(5), 577–597. https://doi.org/10.1080/03088839.2020.1788731
Murray, B., & Perera, L. P. (2020). A dual linear autoencoder approach for vessel trajectory prediction using historical AIS data. Ocean Engineering, 209, 107478. https://doi.org/10.1016/j.oceaneng.2020.107478
Nisa, K. S., Suendo, V., Sophiana, I. C., Susanto, H., Kusumaatmaja, A., Nishiyama, N., & Budhi, Y. W. (2022). Effect of base promoter on activity of MCM-41-supported nickel catalyst for hydrogen production via dry reforming of methane. International Journal of Hydrogen Energy, 47(47), 23201–23212. https://doi.org/10.1016/j.ijhydene.2022.05.081
Oloruntobi, O., Mokhtar, K., Gohari, A., Asif, S., & Chuah, L. F. (2023). Sustainable transition towards greener and cleaner seaborne shipping industry: Challenges and opportunities. Cleaner Engineering and Technology, 13, 100628. https://doi.org/10.1016/j.clet.2023.100628
Ourdas, C., & Ponis, S. (2023). Evaluating the effects of gamification in behavioral change: A proposed SEM-based approach. Sustainability, 15, 5442. https://doi.org/10.3390/su15065442
Perumal, K., Boopathi, V., Chellaiyan, S., Muthuramalingam, S., & Raja, P. (2021). Sources, spatial distribution, and abundance of marine debris on Thondi coast, Palk Bay, Southeast coast of India. Environmental Sciences Europe, 33, Article 136. https://doi.org/10.1186/s12302-021-00576-x
Qiao, D., Liu, G., Lv, T., Li, W., & Zhang, J. (2021). Marine vision-based situational awareness using discriminative deep learning: A survey. Journal of Marine Science and Engineering, 9(4), 397. https://doi.org/10.3390/jmse9040397
Ranyal, E., Sadhu, A., & Jain, K. (2022). Road condition monitoring using smartsensing and artificial intelligence: A review. Sensors, 22(8), 3044. https://doi.org/10.3390/s22083044
Sánchez-González, P.-L., Díaz-Gutiérrez, D., Leo, T. J., & Núñez-Rivas, L. R. (2019). Toward digitalization of maritime transport? Sensors, 19(4), 926. https://doi.org/10.3390/s19040926
Selig, E. R., Nakayama, S., Wabnitz, C. C. C., Österblom, H., Spijkers, J., Miller, N. A., Bebbington, J., & Decker Sparks, J. L. (2022). Revealing global risks of labor abuse and illegal, unreported, and unregulated fishing. Nature Communications, 13, 1612. https://doi.org/10.1038/s41467-022-28916-2
Shadman, M., Roldan-Carvajal, M., Pierart, F. G., Haim, P. A., Alonso, R., Silva, C., Osorio, A. F., Almonacid, N., Carreras, G., Maali Amiri, M., Arango-Aramburo, S., Rosas, M. A., Pelissero, M., Tula, R., Estefen, S. F., Pastor, M. L., & Saavedra, O. R. (2023). A review of offshore renewable energy in South America: Current status and future perspectives. Sustainability, 15, 1740. https://doi.org/10.3390/su15021740
Siddiqua, A., Hahladakis, J. N., & AlAttiya, W. A. K. (2022). An overview of the environmental pollution and health effects associated with waste landfilling and open dumping. Environmental Science and Pollution Research, 29(43), 58514–58536. https://doi.org/10.1007/s11356-022-21578-z
Smeaton, C., Hunt, C. A., Turrell, W. R., & Austin, W. E. N. (2021). Marine sedimentary carbon stocks of the United Kingdom's Exclusive Economic Zone. Frontiers in Earth Science, 9, 593324. https://doi.org/10.3389/feart.2021.593324
Son, B. A. (2023). Rise of constabulary maritime agencies in Southeast Asia: Vietnam's paragunboat diplomacy in the North Natuna Seas. Social Sciences, 12(4), 241. https://doi.org/10.3390/socsci12040241
Sui, B., Zhang, J., & Liu, Z. (2023). A real-time ship encounter collision risk detection approach in close-quarters situation. Measurement and Control, 56(9–10), 1613–1625. https://doi.org/10.1177/00202940231175086
Thangavel, K., Servidia, P., Sabatini, R., Marzocca, P., Fayek, H., Cerruti, S. H., España, M., & Spiller, D. (2023). A distributed satellite system for multibaseline AT-InSAR: Constellation of formations for maritime domain awareness using autonomous orbit control. Aerospace, 10(2), 176. https://doi.org/10.3390/aerospace10020176
Thombre, S., Zhao, Z., Ramm-Schmidt, H., Vallet García, J. M., Malkamäki, T., Nikolskiy, S., Hammarberg, T., Nuortie, H., Bhuiyan, M. Z. H., Särkkä, S., & Lehtola, V. V. (2022). Sensors and AI techniques for situational awareness in autonomous ships: A review. IEEE Transactions on Intelligent Transportation Systems, 23(1), 64–79. https://doi.org/10.1109/TITS.2020.3023957
Trongtirakul, T., Agaian, S., Oulefki, A., & Panetta, K. (2023). Method for remote sensing oil spill applications over thermal and polarimetric imagery. IEEE Journal of Oceanic Engineering, 48(3), 973–987. https://doi.org/10.1109/JOE.2023.3245759
Vairo, T., Cademartori, D., Clematis, D., Carpanese, M. P., & Fabiano, B. (2023). Solid oxide fuel cells for shipping: A machine learning model for early detection of hazardous system deviations. Process Safety and Environmental Protection, 172, 184–194. https://doi.org/10.1016/j.psep.2023.02.022
Van de Merwe, K., Mallam, S., Nazir, S., & Engelhardtsen, Ø. (2024). Supporting human supervision in autonomous collision avoidance through agent transparency. Safety Science, 169, 106329. https://doi.org/10.1016/j.ssci.2023.106329
Veitch, E., & Alsos, O. A. (2022). A systematic review of human-AI interaction in autonomous ship systems. Safety Science, 152, 105778. https://doi.org/10.1016/j.ssci.2022.105778
Venskus, J., Treigys, P., & Markevičiūtė, J. (2021). Unsupervised marine vessel trajectory prediction using LSTM network and wild bootstrapping techniques. Nonlinear Analysis: Modeling and Control, 26(4), 718–737. https://doi.org/10.15388/namc.2021.26.23056
Yates, D., & Brodie, N. (2023). The illicit trade in antiquities is not the world's third-largest illicit trade: A critical evaluation of a factoid. Antiquity, 97(394), 991–1003. https://doi.org/10.15184/aqy.2023.90
Zhao, C., Fu, X., Dong, J., Feng, C., & Chang, H. (2023). LPDNet: A lightweight network for SAR ship detection based on multi-level Laplacian denoising. Sensors, 23(13), 6084. https://doi.org/10.3390/s23136084
Burmeister, H.-C., & Constapel, M. (2021). Autonomous collision avoidance at sea: A survey. Frontiers in Robotics and AI, 8, 739013. https://doi.org/10.3389/frobt.2021.739013
Chen, X., Xu, Q., & Li, L. (2023). Illegal, unreported, and unregulated fishing governance in disputed maritime areas: Reflections on the international legal obligations of states. Fishes, 8(1), 36. https://doi.org/10.3390/fishes8010036
Choi, E. C. (2023). Investigating the management of marine sand mining: A case of West Sea Exclusive Economic Zone in South Korea. Regional Studies in Marine Science, 66, 103109. https://doi.org/10.1016/j.rsma.2023.103109
Coventry, T. (2023). Seizing stateless smuggling vessels on the Mediterranean High Seas. Leiden Journal of International Law, 36(4), 925–946. https://doi.org/10.1017/S092215652300016X
Escalle, L., Mourot, J., Hamer, P., Hare, S. R., Phillip Jr., N. B., & Pilling, G. M. (2023). Towards non-entangling and biodegradable drifting fish aggregating devices – Baselines and transition in the world's largest tuna purse seine fishery. Marine Policy, 149, 105500. https://doi.org/10.1016/j.marpol.2023.105500
Fang, B., Yu, J., Chen, Z., Osman, A. I., Farghali, M., Ihara, I., Hamza, E. H., Rooney, D. W., & Yap, P.-S. (2023). Artificial intelligence for waste management in smart cities: A review. Environmental Chemistry Letters, 21, 1959–1989. https://doi.org/10.1007/s10311-023-01604-3
Goodman, A. J., Walker, T. R., Brown, C. J., Wilson, B. R., Gazzola, V., & Sameoto, J. A. (2020). Benthic marine debris in the Bay of Fundy, eastern Canada: Spatial distribution and categorization using seafloor video footage. Marine Pollution Bulletin, 150, 110722. https://doi.org/10.1016/j.marpolbul.2019.110722
Grønsund, T., & Aanestad, M. (2020). Augmenting the algorithm: Emerging human-in-the-loop work configurations. Journal of Strategic Information Systems, 29(3), 101614. https://doi.org/10.1016/j.jsis.2020.101614
Harris, J. L., Collins, C., Spalding, M., & Stevens, G. M. W. (2024). First records of the sicklefin (Mobula tarapacana), bentfin (Mobula thurstoni), and spinetail (Mobula mobular) devil rays in the Chagos Archipelago. Journal of Fish Biology, 104(6), 1628–1632. https://doi.org/10.1111/jfb.15678
He, Z., Wang, C., Gao, J., & Xie, Y. (2023). Assessment of global shipping risk caused by maritime piracy. Heliyon, 9, e20988. https://doi.org/10.1016/j.heliyon.2023.e20988
Ichimura, Y., Dalaklis, D., Kitada, M., & Christodoulou, A. (2022). Shipping in the era of digitalization: Mapping the future strategic plans of major maritime commercial actors. Digital Business, 2, 100022. https://doi.org/10.1016/j.digbus.2022.100022
Jang, J.-G., Noh, C.-M., Kim, S.-S., Shin, S.-C., Lee, S.-S., & Lee, J.-C. (2022). Vibration data feature extraction and deep learning-based preprocessing method for highly accurate motor fault diagnosis. Journal of Computational Design and Engineering, 10(1), 204–220. https://doi.org/10.1093/jcde/qwac128
Khobragade, J. W., Kumar, A., Abd Aziz, S. N. B., & Maurya, D. (2021). The anti-maritime piracy law in India and Malaysia: An analytical study. Journal of International Maritime Safety, Environmental Affairs, and Shipping, 5(4), 208–219. https://doi.org/10.1080/25725084.2021.2006462
Liu, X. (2022). The supervision and multi-sectoral guarantee mechanism of the global marine sulfur limit—Assessment from Chinese shipping industry. Frontiers in Marine Science, 9, 1028388. https://doi.org/10.3389/fmars.2022.1028388
Moreno, G., Salvador, J., Zudaire, I., Murua, J., Pelegrí, J. L., Uranga, J., Murua, H., Grande, M., Santiago, J., & Restrepo, V. (2023). The Jelly-FAD: A paradigm shift in the design of biodegradable fish aggregating devices. Marine Policy, 147, 105352. https://doi.org/10.1016/j.marpol.2022.105352
Munim, Z. H., Dushenko, M., Jimenez, V. J., Shakil, M. H., & Imset, M. (2020). Big data and artificial intelligence in the maritime industry: A bibliometric review and future research directions. Maritime Policy & Management, 47(5), 577–597. https://doi.org/10.1080/03088839.2020.1788731
Murray, B., & Perera, L. P. (2020). A dual linear autoencoder approach for vessel trajectory prediction using historical AIS data. Ocean Engineering, 209, 107478. https://doi.org/10.1016/j.oceaneng.2020.107478
Nisa, K. S., Suendo, V., Sophiana, I. C., Susanto, H., Kusumaatmaja, A., Nishiyama, N., & Budhi, Y. W. (2022). Effect of base promoter on activity of MCM-41-supported nickel catalyst for hydrogen production via dry reforming of methane. International Journal of Hydrogen Energy, 47(47), 23201–23212. https://doi.org/10.1016/j.ijhydene.2022.05.081
Oloruntobi, O., Mokhtar, K., Gohari, A., Asif, S., & Chuah, L. F. (2023). Sustainable transition towards greener and cleaner seaborne shipping industry: Challenges and opportunities. Cleaner Engineering and Technology, 13, 100628. https://doi.org/10.1016/j.clet.2023.100628
Ourdas, C., & Ponis, S. (2023). Evaluating the effects of gamification in behavioral change: A proposed SEM-based approach. Sustainability, 15, 5442. https://doi.org/10.3390/su15065442
Perumal, K., Boopathi, V., Chellaiyan, S., Muthuramalingam, S., & Raja, P. (2021). Sources, spatial distribution, and abundance of marine debris on Thondi coast, Palk Bay, Southeast coast of India. Environmental Sciences Europe, 33, Article 136. https://doi.org/10.1186/s12302-021-00576-x
Qiao, D., Liu, G., Lv, T., Li, W., & Zhang, J. (2021). Marine vision-based situational awareness using discriminative deep learning: A survey. Journal of Marine Science and Engineering, 9(4), 397. https://doi.org/10.3390/jmse9040397
Ranyal, E., Sadhu, A., & Jain, K. (2022). Road condition monitoring using smartsensing and artificial intelligence: A review. Sensors, 22(8), 3044. https://doi.org/10.3390/s22083044
Sánchez-González, P.-L., Díaz-Gutiérrez, D., Leo, T. J., & Núñez-Rivas, L. R. (2019). Toward digitalization of maritime transport? Sensors, 19(4), 926. https://doi.org/10.3390/s19040926
Selig, E. R., Nakayama, S., Wabnitz, C. C. C., Österblom, H., Spijkers, J., Miller, N. A., Bebbington, J., & Decker Sparks, J. L. (2022). Revealing global risks of labor abuse and illegal, unreported, and unregulated fishing. Nature Communications, 13, 1612. https://doi.org/10.1038/s41467-022-28916-2
Shadman, M., Roldan-Carvajal, M., Pierart, F. G., Haim, P. A., Alonso, R., Silva, C., Osorio, A. F., Almonacid, N., Carreras, G., Maali Amiri, M., Arango-Aramburo, S., Rosas, M. A., Pelissero, M., Tula, R., Estefen, S. F., Pastor, M. L., & Saavedra, O. R. (2023). A review of offshore renewable energy in South America: Current status and future perspectives. Sustainability, 15, 1740. https://doi.org/10.3390/su15021740
Siddiqua, A., Hahladakis, J. N., & AlAttiya, W. A. K. (2022). An overview of the environmental pollution and health effects associated with waste landfilling and open dumping. Environmental Science and Pollution Research, 29(43), 58514–58536. https://doi.org/10.1007/s11356-022-21578-z
Smeaton, C., Hunt, C. A., Turrell, W. R., & Austin, W. E. N. (2021). Marine sedimentary carbon stocks of the United Kingdom's Exclusive Economic Zone. Frontiers in Earth Science, 9, 593324. https://doi.org/10.3389/feart.2021.593324
Son, B. A. (2023). Rise of constabulary maritime agencies in Southeast Asia: Vietnam's paragunboat diplomacy in the North Natuna Seas. Social Sciences, 12(4), 241. https://doi.org/10.3390/socsci12040241
Sui, B., Zhang, J., & Liu, Z. (2023). A real-time ship encounter collision risk detection approach in close-quarters situation. Measurement and Control, 56(9–10), 1613–1625. https://doi.org/10.1177/00202940231175086
Thangavel, K., Servidia, P., Sabatini, R., Marzocca, P., Fayek, H., Cerruti, S. H., España, M., & Spiller, D. (2023). A distributed satellite system for multibaseline AT-InSAR: Constellation of formations for maritime domain awareness using autonomous orbit control. Aerospace, 10(2), 176. https://doi.org/10.3390/aerospace10020176
Thombre, S., Zhao, Z., Ramm-Schmidt, H., Vallet García, J. M., Malkamäki, T., Nikolskiy, S., Hammarberg, T., Nuortie, H., Bhuiyan, M. Z. H., Särkkä, S., & Lehtola, V. V. (2022). Sensors and AI techniques for situational awareness in autonomous ships: A review. IEEE Transactions on Intelligent Transportation Systems, 23(1), 64–79. https://doi.org/10.1109/TITS.2020.3023957
Trongtirakul, T., Agaian, S., Oulefki, A., & Panetta, K. (2023). Method for remote sensing oil spill applications over thermal and polarimetric imagery. IEEE Journal of Oceanic Engineering, 48(3), 973–987. https://doi.org/10.1109/JOE.2023.3245759
Vairo, T., Cademartori, D., Clematis, D., Carpanese, M. P., & Fabiano, B. (2023). Solid oxide fuel cells for shipping: A machine learning model for early detection of hazardous system deviations. Process Safety and Environmental Protection, 172, 184–194. https://doi.org/10.1016/j.psep.2023.02.022
Van de Merwe, K., Mallam, S., Nazir, S., & Engelhardtsen, Ø. (2024). Supporting human supervision in autonomous collision avoidance through agent transparency. Safety Science, 169, 106329. https://doi.org/10.1016/j.ssci.2023.106329
Veitch, E., & Alsos, O. A. (2022). A systematic review of human-AI interaction in autonomous ship systems. Safety Science, 152, 105778. https://doi.org/10.1016/j.ssci.2022.105778
Venskus, J., Treigys, P., & Markevičiūtė, J. (2021). Unsupervised marine vessel trajectory prediction using LSTM network and wild bootstrapping techniques. Nonlinear Analysis: Modeling and Control, 26(4), 718–737. https://doi.org/10.15388/namc.2021.26.23056
Yates, D., & Brodie, N. (2023). The illicit trade in antiquities is not the world's third-largest illicit trade: A critical evaluation of a factoid. Antiquity, 97(394), 991–1003. https://doi.org/10.15184/aqy.2023.90
Zhao, C., Fu, X., Dong, J., Feng, C., & Chang, H. (2023). LPDNet: A lightweight network for SAR ship detection based on multi-level Laplacian denoising. Sensors, 23(13), 6084. https://doi.org/10.3390/s23136084
Published
2025-10-09
How to Cite
Cintya Yelena Putri, A. Adang Supriyadi, & Abdul Rivai Ras. (2025). Artificial Intelligence and Maritime Governance: Policy Challenges in Combating Illegal Fishing in the Natuna Exclusive Economic Zone. International Journal of Education, Vocational and Social Science , 4(04), 303-320. https://doi.org/10.63922/ijevss.v4i04.2368
Contact Person +6282139474255
Email : ijevss@citakonsultindo.or.id / editor.ijevss@gmail.com
