Improving Vegetable Production in North Aceh Regency: An Implementation of a Smart Farming Monitoring System
DOI:
https://doi.org/10.35877/454RI.jinav4322Keywords:
Smart Farming; Vegetable; IoT; Productivity.Abstract
This research aims to design and implement a smart farming monitoring system that is appropriate for the local conditions of North Aceh to optimize the production of leading vegetables and facilitate sustainable agricultural transformation. In line with the national agenda toward the digitalization of the agricultural sector, this research is part of a concrete effort to encourage the adoption of smart farming technology at the local level. North Aceh Regency has great horticultural potential, but it is not yet optimal due to the minimal application of technology. This research supports the development of agriculture based on local potential. The study also promotes a participatory and educative approach to increase farmers' digital literacy and reduce the technology gap between conventional and modern technology-adopting farmers. The Smart Farming monitoring system was successfully implemented using soil moisture, air temperature, soil pH, and light intensity sensors integrated into a web-based dashboard and mobile application. The implementation of this system was able to increase vegetable productivity by 18–22%, especially for mustard greens, chili, and tomatoes, compared to conventional methods. The system also contributed to the efficient use of resources, shown by a 25% savings in irrigation water and a 15% reduction in the use of chemical fertilizers. The farmer response was quite positive, although there are still challenges related to digital literacy among some older farmers. Overall, the implementation of Smart Farming in North Aceh Regency had a real impact on increasing productivity and cost efficiency while supporting sustainable agriculture in line with the SDGs.
References
Faridhatul ulva, a., abdullah, d., masriadi, nurhasanah, alimul haq, n., & ulumul haq, b. (2023). Aros(agro-smart)?: smart city pertanian dengan track and trace gps berbasis mobile. Jurnal informasi dan teknologi, 5(4), 78–91. Https://doi.org/10.60083/jidt.v5i4.418
Hersydano, m. R., pamungkas, s. G., putra, i. G. L. D., rahman, a., & warohma, a. M. (2025). Rancangan sistem monitoring greenhouse hidroponik berbasis iot. Mdp student conference, 4(1), 483–490. Https://doi.org/10.35957/mdp-sc.v4i1.11234
Napolitano, e. V., masciari, e., & ordonez, c. (2024). Integrating flow and structure in diagrams for data science. Proceedings - 2024 ieee international conference on big data, bigdata 2024, 5769–5774. Https://doi.org/10.1109/bigdata62323.2024.10826098
Nunsina, n., nurdin, n., darnila, e., & fitri, z. (2025). Implementasi smart village berbasis iot dalam meningkatkan kemandirian desa di kabupaten bireuen. Teknika, 19(1), 37–45. Https://doi.org/10.5281/zenodo.13777632
Nunsina, n., zuhra, f., & yunizar, z. (2024). Sosialisasi peningkatan kualitas produktivitas panen udang melalui pengontrolan kadar air berbasis iot di desa kuala ceurape. Rambideun?: jurnal pengabdian kepada masyarakat, 7(1), 57–64. Https://doi.org/10.51179/pkm.v7i1.2417


