Nur Annisa Putri Nazaruddin
Universitas Hasanuddin

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Edufarming Communication Strategy for The Diffusion of Smart Farming Innovation: A Qualitative Case Study of SGH Hydroponic Nur Annisa Putri Nazaruddin; Moehammad Iqbal Sultan; Andi Subhan Amir
Jambura Agribusiness Journal VOLUME 7, ISSUE 2, 2026: JANUARY-JUNE
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37046/jaj.v7i2.38587

Abstract

This study analyzes Edufarming as a communication strategy for diffusing AIoT-based smart farming innovation at SGH Hydroponic in Gowa Regency, South Sulawesi, Indonesia. The study employed a qualitative approach with a descriptive single-case study design. Data were collected through semi-structured interviews, participant observation, and documentation. The informants consisted of the founder, co-founder, two technical staff members of SGH Hydroponic, and one participant in the Edufarming program. The researcher also participated directly in the Edufarming program to observe the learning process, interaction patterns, and technology demonstrations. Data were analyzed using an interactive qualitative model consisting of data collection, data condensation, data display, and conclusion drawing. The analysis also applied thematic categorization based on Rogers’ diffusion of innovation attributes and was strengthened through source and methodological triangulation. The findings show that Edufarming functions not only as an agricultural education activity but also as a participatory communication mechanism that connects technology, agribusiness actors, training participants, and market partners within a learning ecosystem. The diffusion process occurs through technology demonstrations, hands-on practice, interpersonal communication, group learning, and direct observation of production outcomes. AIoT-based hydroponics provides relative advantages through production stability, faster harvesting, product consistency, and stronger market trust. Edufarming also improves compatibility, reduces perceived complexity, facilitates trialability, and strengthens observability through visible plant growth, dashboard-based monitoring, and practical learning activities. The study implies that smart farming diffusion requires technological readiness, structured communication, mentoring, digital literacy support, and participatory learning.