Technology-Based Fish Health Service Innovation for Sustainable Aquaculture Practices in Indonesia

Authors

  • Fadlil Ferdiansyah Department of Computer Engineering, Faculty of Engineering, Diponegoro University, Semarang, Indonesia
  • Irawan Habib Yulianto Department of Computer Engineering, Faculty of Engineering, Diponegoro University, Semarang, Indonesia
  • Muhammad Zamrol Imada Department of Computer Engineering, Faculty of Engineering, Diponegoro University, Semarang, Indonesia
  • Patricia Evericho Mountaines Department of Computer Engineering, Faculty of Engineering, Diponegoro University, Semarang, Indonesia
  • Erwin Adriono Department of Computer Engineering, Faculty of Engineering, Diponegoro University, Semarang, Indonesia
  • Yudi Eko Windarto Department of Computer Engineering, Faculty of Engineering, Diponegoro University, Semarang, Indonesia
  • Arseto Satriyo Nugroho Department of Computer Engineering, Faculty of Engineering, Diponegoro University, Semarang, Indonesia

DOI:

https://doi.org/10.12928/spekta.v6i2.13492

Keywords:

Aquaculture, Artificial Intelligence, Expert System, Fish Disease Diagnosis, Progressive Web App

Abstract

Background: Indonesia’s aquaculture sector holds vast potential, yet many fish farmers, especially those in remote areas like offshore cages, face limited access to timely fish health services, leading to undetected disease outbreaks, mass fish mortality, and significant economic losses.

Contribution: This study introduces Fish Doctor, a scalable platform integrating fish species detection, disease diagnosis, and expert consultation. It bridges the gap between AI-based detection and practical aquaculture needs in developing countries, supporting sustainable practices aligned with SDG 2 (Zero Hunger) and SDG 12 (Responsible Consumption and Production).

Method: The application was built using Next.js, Express.js, MySQL, and integrates computer vision and expert systems. Its core features include image-based fish species detection using YOLOv11, rule-based disease diagnosis through forward chaining, and an online expert consultation module.  Designed as a Progressive Web App (PWA), the system offers offline-first capabilities, enabling its use in low-connectivity environments.

Results: The system was evaluated using test datasets of five fish species, achieving an average diagnostic accuracy above 80% and response times of less than 2 seconds per case.

Conclusion: The developed platform demonstrates potential for improving early disease detection and reducing reliance on chemical treatments in aquaculture. Future research will involve usability testing with more than 100 fish farmers across multiple provinces to assess scalability and generalizability.

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Published

2025-12-20

How to Cite

Ferdiansyah, F., Yulianto, I. H., Imada, M. Z., Mountaines, P. E., Adriono, E., Windarto, Y. E., & Nugroho, A. S. (2025). Technology-Based Fish Health Service Innovation for Sustainable Aquaculture Practices in Indonesia. SPEKTA (Jurnal Pengabdian Kepada Masyarakat : Teknologi Dan Aplikasi), 6(2), 407–422. https://doi.org/10.12928/spekta.v6i2.13492

Issue

Vol. 6 No. 2 (2025)

Section

Product Design and Development

License

Copyright (c) 2025 Fadlil Ferdiansyah, Irawan Habib Yulianto, Muhammad Zamrol Imada, Patricia Evericho Mountaines, Erwin Adriono, Yudi Eko Windarto, Arseto Satriyo Nugroho

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