Evaluation of Usage Behaviour of IOT-Based Aquaculture Technologies


  • Mangaras Yanu Florestiyanto
  • Panji Dwi Ashrianto
  • Bambang Yuwono
  • Hidayatulah Himawan




Iot, Adopting Intention, Usage Behavior


The production of aquaculture products still needs to be increased to match marine products. One of the problems that cause cultivation fishery production is not optimal is that it has not utilized modern technology. Cultivators still use traditional methods and technologies in cultivation. One of the contemporary technologies that can support aquaculture is Automation Technology and the Internet of Things (IoT). This research will develop an IoT-based technology, which is a system to help fish maintenance management. This system is based on a static robot that will monitor the condition of pond water quality and feed the fish automatically, which can be controlled remotely by adopting an IoT architecture.Furthermore, an evaluation of cultivators/farmers regarding Adopting Intention (AI) of this technology. The evaluation model adopted the model proposed by (Kao et al., 2019). This model explores the direct influence of perceived usability, performance expectations, perceived technology usefulness, network externality, user creativity, and domain-specific information on intent and their indirect impact on user behavior.


Abinaya, T., Ishwarya, J. and Maheswari, M. (2019) 'A Novel Methodology for Monitoring and Controlling of Water Quality in Aquaculture using Internet of Things' (IoT)', in 2019 International Conference on Computer Communication and Informatics (ICCCI), pp. 1–4.

Africa, A. D. M. et al. (2017) ‘Automated aquaculture system that regulates Ph, temperature and ammonia’, in 2017 IEEE 9th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment and Management (HNICEM). Manila: IEEE, pp. 1–6.

Bryman, A. (2016) Quantity And Quality In Social Research. Taylor & Francis.

Budiman, F., Rivai, M. and Nugroho, M. A. (2019) ‘Monitoring and Control System for Ammonia and pH Levels for Fish Cultivation Implemented on Raspberry Pi 3B’, Proceedings - 2019 International Seminar on Intelligent Technology and Its Application, ISITIA 2019, pp. 68–73. DOI: 10.1109/ISITIA.2019.8937217.

CST, U. O., Djunaidah, I. S. and Sinaga, W. H. (2019) ‘Analisis Potensi dan Permasalahan Usaha Perikanan Budidaya di Kecamatan Bungursari Kota Tasikmalaya Provinsi Jawa Barat’, Jurnal Penyuluhan Perikanan dan Kelautan, 13(1), pp. 107–119. doi: 10.33378/jppik.v13i1.119.

Elsaadany, A. and Soliman, M. (2017) ‘Experimental Evaluation of Internet of Things in the Educational Environment’, International Journal of Engineering Pedagogy (iJEP), 7(3), p. 50. DOI: 10.3991/ijep.v7i3.7187.

Hair, J. F. et al. (2017) A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Thousand Oaks: Sage Publications. Available at: https://scholar.google.com/scholar_lookup?title=Advanced+Issues+in+Partial+Least+Squares+Structural+Equation+Modeling&author=Hair,+J.F.,+Jr.&author=Sarstedt,+M.&author=Ringle,+C.M.&author=Gudergan,+S.P.&publication_year=2017.

Hsu, C. L., and Lin, J. C. C. (2016) 'An empirical examination of consumer adoption of Internet of Things services: Network externalities and concern for information privacy perspectives', Computers in Human Behavior. Elsevier Ltd, 62, pp. 516–527. DOI: 10.1016/j.chb.2016.04.023.

Hsu, W. W. Y. et al. (2019) ‘Portable Fisheries Assistant Systems for Small Scale Fisheries Management’, in 2019 IEEE Eurasia Conference on IoT, Communication, and Engineering (ECICE), pp. 10–13.

Ichtifa, N., Wiryati, G. and Anas, P. (2019) ‘Potensi dan Permasalahan Perikanan Budidaya di Kecamatan Caringin Kabupaten Sukabumi Provinsi Jawa Barat’, Jurnal Penyuluhan Perikanan dan Kelautan, 13(1), pp. 11–27. doi: 10.33378/jppik.v13i1.121.

Kao, Y. S., Nawata, K. and Huang, C. Y. (2019) 'An exploration and confirmation of the factors influencing adoption of IoT-based wearable fitness trackers', International Journal of Environmental Research and Public Health, 16(18). DOI: 10.3390/ijerph16183227.

Lafont, M. et al. (2019) ‘Back to the future: IoT to improve aquaculture : Real-time monitoring and algorithmic prediction of water parameters for aquaculture needs’, in 2019 Global IoT Summit (GIoTS), pp. 1–6.

Ma, Y. and Ding, W. (2018) ‘Design of Intelligent Monitoring System for Aquaculture Water Dissolved Oxygen’, in 2018 IEEE 3rd Advanced Information Technology, Electronic and Automation Control Conference (IAEAC), pp. 414–418.

Mwangi, M. and Kariuki, S. (2015) ‘Factors Determining Adoption of New Agricultural Technology by Smallholder Farmers in Developing Countries’, Issn, 6(5), pp. 2222–1700. Available at: www.iiste.org.

Niswar, M. et al. (2018) ‘IoT-based Water Quality Monitoring System for Soft-Shell Crab Farming’, in 2018 IEEE International Conference on Internet of Things and Intelligence System (IOTAIS), pp. 6–9.

Raju, K. R. S. R., and Varma, G. H. K. (2017) 'Knowledge-based real-time monitoring system for aquaculture Using IoT', Proceedings - 7th IEEE International Advanced Computing Conference, IACC 2017. IEEE, pp. 318–321. DOI: 10.1109/IACC.2017.0075.

Zulkarnain, M., Purwanti, P. and Indrayani, E. (2013) ‘Analysis of Aquaculture Production Value Effect To Gross Domestic Product of Fisheries Sector in’, Jurnal ECSOFiM, 1(1), pp. 52–68.