Issue

Vol. 5 No. 1 (2026): Startupreneur Business Digital (SABDA)

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Innovations in Technology and Data Systems to Strengthen Fisheries Management

https://doi.org/10.33050/sabda.v5i1.1045
Rifqi Fahrudin
University of Catur Insan Cendekia
https://orcid.org/0000-0001-9782-7204
Royani
University of Ichsan Satya
https://orcid.org/0000-0002-2746-5364
Asher Nuche
Ijiis Incorporation
https://orcid.org/0009-0001-1431-2270
Elda Diah Safitri
State University of Jakarta

Corresponding Author(s) : Rifqi Fahrudin

rifqi.fahrudin@cic.ac.id

Startupreneur Business Digital (SABDA Journal), Vol. 5 No. 1 (2026): Startupreneur Business Digital (SABDA)

Abstract

Fisheries management faces critical pressures from overexploitation, climate change, and illegal, unreported, and unregulated (IUU) fishing. Conventional monitoring systems often rely on fragmented and delayed data, which significantly limit effective decision-making. This study examine how emerging digital technologies and advanced data systems enhance governance, transparency, and sustainability in the sector. A mixed-method approach was employed, combining a systematic literature review and a comparative case assessment of technology adoption. The results demonstrate that integrating Electronic Monitoring (EM) and Vessel Monitoring Systems (VMS) can expand monitoring coverage by up to 100% in industrial fleets compared to human observers, while reducing long-term operational costs. Digital reporting platforms (e-logbooks) were found to significantly reduce data transcription errors and shorten the feedback loop between data collection and regulatory action. Furthermore, Artificial Intelligence (AI)-assisted species identification improves the speed of processing catch data from EM footage. However, successful implementation depends on institutional readiness, regulatory alignment, and ensuring equitable digital access for small-scale fishers. This research concludes that while technology holds transformative potential, long-term effectiveness requires integrated governance frameworks and collaborative implementation strategies.

Keywords

Fisheries Management Digital Innovation Advanced Data Systems
Fahrudin, R., Royani, Nuche, A., & Safitri, E. D. (2026). Innovations in Technology and Data Systems to Strengthen Fisheries Management. Startupreneur Business Digital (SABDA Journal), 5(1), 55–66. https://doi.org/10.33050/sabda.v5i1.1045
Download Citation
Endnote/Zotero/Mendeley (RIS)
BibTeX
References
  1. 1] F. Han, Y. Liu, H. Tian, J. Li, and Y. Tian, “A comprehensive framework incorporating deep learning for analyzing fishing vessel activity using automatic identification system data,” ICES Journal of Marine Science, vol. 82, no. 2, p. fsae166, 2025.
  2. [2] T. Garlock, J. L. Anderson, F. Asche, M. D. Smith, E. Camp, J. Chu, K. Lorenzen, and S. Vannuccini, “Global insights on managing fishery systems for the three pillars of sustainability,” Fish and Fisheries, vol. 23, no. 4, pp. 899–909, 2022.
  3. [3] W. Yu, X. Feng, J. Wen, X. Wu, X. Fang, J. Cui, Z. Feng, Y. Sheng, Z. Zhao, B. Liu et al., “The potential impacts of climate change on the life history and habitat of jumbo flying squid in the southeast pacific ocean: Overview and implications for fisheries management,” Reviews in Fish Biology and Fisheries, vol. 35, no. 2, pp. 707–731, 2025.
  4. [4] S. Bhusan, S. Abuthagir Iburahim, J. Akash, T. Paul Nathaniel, and U. Arisekar, “Emerging trends in information technology with reference to fisheries and aquaculture,” Information technology in fisheries and aquaculture, pp. 251–263, 2025.
  5. [5] J. Ma, Z. Wu, M. Guo, and Q. Hu, “Trade-offs between economic gains and ecological goals: Impact of marine ecological policy on marine fisheries efficiency,” Fisheries Management and Ecology, vol. 33, no. 1, pp. 142–157, 2026.
  6. [6] X. Basurto, N. L. Gutierrez, N. Franz, M. d. M. Mancha-Cisneros, G. Gorelli, A. Agui´on, S. Funge-Smith, S. Harper, D. J. Mills, G. Nico et al., “Illuminating the multidimensional contributions of small-scale fisheries,” Nature, vol. 637, no. 8047, pp. 875–884, 2025.
  7. [7] S. Trenggono, I. Meilano, H. Latief, S. Diantara, W. Sakti, D. Ketaren, I. Winata, T. Yuwono, F. Arthatiani, K. Kasim et al., “Innovation in the blue economy and environmental sustainability in marine and fisheries strategy,” Global Journal of Environmental Science and Management, vol. 11, no. 2, pp. 497–518, 2025.
  8. [8] Badan Riset dan Inovasi Nasional, “Policy needs to improve marine capture fish- eries management and to define a role for marine protected areas in indone- sia,” 2024, accessed: 2026-03-10. [Online]. Available: https://data.go.id/dataset/dataset/ policy-needs-to-improve-marine-capture-fisheries-management-and-to-define-a-role-for-marine-pro
  9. [9] F. Asche, T. M. Garlock, J. L. Anderson, R. B. Pincinato, C. M. Anderson, E. V. Camp, J. Chu, A. L. Cojocaru, H. Eggert, K. Lorenzen et al., “A review of global fisheries performance,” Fish and Fisheries, vol. 26, no. 3, pp. 444–453, 2025.
  10. [10] C. M. Free, S. C. Anderson, E. A. Hellmers, B. A. Muhling, M. O. Navarro, K. Richerson, L. A. Rogers, W. H. Satterthwaite, A. R. Thompson, J. M. Burt et al., “Impact of the 2014–2016 marine heatwave on us and canada west coast fisheries: Surprises and lessons from key case studies,” Fish and Fisheries, vol. 24, no. 4, pp. 652–674, 2023.
  11. [11] N. S. Ainy, I. Mujadid, N. Hadi, and L. Sjahfirdi, “Increase in the abundance of invasive fish species in the ciliwung river, dki jakarta and west java provinces,” ADI Journal on Recent Innovation, vol. 6, no. 1, pp. 17–31, 2024.
  12. [12] Kementerian Kelautan dan Perikanan, “Regional fisheries management organizations,” 2024, direktorat Jenderal Perikanan Tangkap, Accessed: 2026-03-10. [Online]. Available: https: //kkp.go.id/unit-kerja/djpt/publikasi/infografis-detail/regional-fisheries-management-organizations.html
  13. [13] X. Cheng, J. Wang, X. Chen, and F. Zhang, “Attention-enhanced and integrated deep learning approach for fishing vessel classification based on multiple features,” Scientific Reports, vol. 15, no. 1, p. 8642, 2025.
  14. [14] M. Yao, S. Zhang, Q. Lu, X. Chen, S.-Y. Zhang, Y. Kong, and J. Zhao, “Fishing for fish environmen- tal dna: Ecological applications, methodological considerations, surveying designs, and ways forward,” Molecular ecology, vol. 31, no. 20, pp. 5132–5164, 2022.
  15. [15] A. March and P. Failler, “Small-scale fisheries development in africa: Lessons learned and best practices for enhancing food security and livelihoods,” Marine Policy, vol. 136, p. 104925, 2022.
  16. [16] P. Li, H. Han, S. Zhang, H. Fang, W. Fan, F. Zhao, and C. Xu, “Reviews on the development of digital intelligent fisheries technology in aquaculture,” Aquaculture International, vol. 33, no. 3, p. 191, 2025.
  17. [17] N. Pacoureau, J. K. Carlson, H. K. Kindsvater, C. L. Rigby, H. Winker, C. A. Simpfendorfer, P. Charvet, R. A. Pollom, R. Barreto, C. S. Sherman et al., “Conservation successes and challenges for wide-ranging sharks and rays,” Proceedings of the National Academy of Sciences, vol. 120, no. 5, p. e2216891120, 2023.
  18. [18] T. Rochefort and Z. Ndlovu, “Digital marketing strategies in building brand awareness and loyalty in the online era,” Startupreneur Business Digital (SABDA Journal), vol. 3, no. 2, pp. 107–114, 2024.
  19. [19] S. Su, Y. Tang, J. P. Kritzer, and Y. Chen, “Using systems thinking to diagnose science-based fisheries management in china,” Marine Policy, vol. 138, p. 104974, 2022.
  20. [20] A. Belhadi, S. Kamble, N. Subramanian, R. K. Singh, and M. Venkatesh, “Digital capabilities to manage agri-food supply chain uncertainties and build supply chain resilience during compounding geopolitical disruptions,” International Journal of Operations & Production Management, vol. 44, no. 11, pp. 1914– 1950, 2024.
  21. [21] P. Danvirutai, S. Charoenwattanasak, S. Tola, K. Thaiso, B. Yuangsoi, H. T. Minh, and C. Srichan, “An integrating rag-llm and deep q-network framework for intelligent fish control systems,” Scientific Reports, vol. 15, no. 1, p. 21377, 2025.
  22. [22] S. Ragab, S. H. Hoseinifar, H. Van Doan, W. Rossi, S. Davies, M. Ashour, and E. El-Haroun, “Overview of aquaculture artificial intelligence (aai) applications: Enhance sustainability and productivity, reduce labor costs, and increase the quality of aquatic products,” Annals of Animal Science, vol. 25, no. 2, pp. 441–453, 2025.
  23. [23] R. Ahli, M. F. Hilmi, and A. Abudaqa, “Moderating effect of perceived organizational support on the relationship between employee performance and its determinants: A case of entrepreneurial firms in uae,” Aptisi Transactions on Technopreneurship (ATT), vol. 6, no. 2, pp. 199–212, 2024.
  24. [24] P. Smallhorn-West, P. J. Cohen, M. Phillips, S. D. Jupiter, H. Govan, and R. L. Pressey, “Linking small- scale fisheries co-management to un sustainable development goals,” Conservation Biology, vol. 36, no. 6, p. e13977, 2022.
  25. [25] A. Suherman, Y. Hernuryadin, P. Suadela, U. A. Furkon, and T. Amboro, “Transformation of indonesian capture fisheries governance: Review and prospects,” Marine Policy, vol. 174, p. 106619, 2025.
  26. [26] M.-C. Chiu, W.-M. Yan, S. A. Bhat, and N.-F. Huang, “Development of smart aquaculture farm management system using iot and ai-based surrogate models,” journal of Agriculture and Food Research, vol. 9, p. 100357, 2022.
  27. [27] S. Balasubramaniam, C. Vijesh Joe, A. Prasanth, and K. S. Kumar, “Computer vision systems in livestock farming, poultry farming, and fish farming: applications, use cases, and research directions,” Computer Vision in Smart Agriculture and Crop Management, pp. 221–258, 2025.
  28. [28] A. D. Garcia, A. M. Rosyid, M. Yusup, and M. Khasanah, “Product innovation of foodpreneurs towards customer loyalty,” Startupreneur Business Digital (SABDA Journal), vol. 4, no. 2, pp. 104–113, 2025.
  29. [29] C. Violette, J. Lucas, C. Assan, J. Lebranchu, and P. Cauquil, “Enhancing fisheries management through data integration: A case study of the seychelles fisheries,” Tech. Rep., 2025.
  30. [30] A. T. Landge, A. Mano, Akansha, K. Nikhil, and S. Abuthagir Iburahim, “Iot and ai applications in fishing: Smart fishing for sustainable practices,” in Information Technology in Fisheries and Aquaculture. Springer, 2025, pp. 59–70.
  31. [31] P. Kumar and P. K. Shukla, “Hybrid transformer cnn model for precise fish segmentation, localization, and species classification in aquaculture,” Journal of Integrated Science and Technology, vol. 13, no. 6, pp. 1134–1134, 2025.
  32. [32] A. G. Prawiyogi, M. Hammet, and A. Williams, “Visualization guides in the understanding of theoretical material in lectures,” International Journal of Cyber and IT Service Management, vol. 3, no. 1, pp. 54–60, 2023.
  33. [33] N. T. Hintzen, K. Brigden, H.-J. Kaastra, S. Mackinson, M. A. Pastoors, and L. Van de Pol, “Bias in global fishing watch ais data analyses results in overestimate of northeast atlantic pelagic fishing impact,” ICES Journal of Marine Science, vol. 82, no. 3, p. fsaf033, 2025.
  34. [34] V. Biazi and C. Marques, “Industry 4.0-based smart systems in aquaculture: A comprehensive review,” Aquacultural Engineering, vol. 103, p. 102360, 2023.
  35. [35] A. Oloko, I. Dahmouni, P. Le Billon, L. Teh, W. Cheung, A. S´anchez-Jim´enez, I. Issifu, and U. R. Sumaila, “Gender dynamics, climate change threats and illegal, unreported, and unregulated fishing,” Discover Sustainability, vol. 6, no. 1, p. 494, 2025.
  36. [36] S. Pratama and L. A. M. Nelloh, “Leveraging influencer marketing in higher education: Key roles, sectors, platforms, and influencer types for institutional branding,” Startupreneur Business Digital (SABDA Journal), vol. 4, no. 2, pp. 134–145, 2025.
  37. [37] S. A. Osinga, D. Paudel, S. A. Mouzakitis, and I. N. Athanasiadis, “Big data in agriculture: Between opportunity and solution,” Agricultural systems, vol. 195, p. 103298, 2022.
  38. [38] L. Marsaglia, A. Parisi, S. Libralato, N. A. Miller, P. Davis, F. S. Paolo, F. Fiorentino, G. Garofalo, M. Costantini, and T. Russo, “Shedding light on trawl fishing activity in the mediterranean sea with remote sensing data,” ICES Journal of Marine Science, vol. 82, no. 2, p. fsae153, 2025.
  39. [39] I. Kilinc, B. Kilinc, C. Takma, and Y. Gevrekci, “Smart tools and artificial intelligence for enhanced quality and safety in agriculture, fisheries, and aquaculture: A review,” Iranian Journal of Fisheries Sciences, vol. 24, no. 4, pp. 913–951, 2025.
  40. [40] K. Zhang, L. Su, Z. Chen, and Y. Qiu, “An extensive assessment of exploitation indicators for multispecies fisheries in the south china sea to inform more practical and precise management in china,” Ecological Indicators, vol. 173, p. 113363, 2025.
  41. [41] D. Li and L. Du, “Recent advances of deep learning algorithms for aquacultural machine vision systems with emphasis on fish,” Artificial Intelligence Review, vol. 55, no. 5, pp. 4077–4116, 2022.
  42. [42] S. Orofino, G. McDonald, J. Mayorga, C. Costello, and D. Bradley, “Opportunities and challenges for improving fisheries management through greater transparency in vessel tracking,” ICES Journal of Marine Science, vol. 80, no. 4, pp. 675–689, 2023.
  43. [43] A. T. Panudju, S. Rahardja, M. Nurilmala et al., “Decision support system in fisheries industry: Cur- rent state and future agenda.” International Journal on Advanced Science, Engineering & Information Technology, vol. 13, no. 2, 2023.
  44. [44] D. M. V. Salac, R. M. A. Salac, and F. G. Destreza, “A web-based system for enhanced fishery man- agement and monitoring with analytics,” in 2023 24th International Arab Conference on Information Technology (ACIT). IEEE, 2023, pp. 1–7.
Read More
Author biographies is not available.
Download this PDF file
PDF
Statistic
Read Counter : 0 Download : 0

Downloads

Download data is not yet available.