Komara, Jaomal
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Determinan Tingkat Adopsi Smart Farming dan Dampaknya terhadap Produktivitas serta Keberlanjutan Usahatani Hortikultura Komara, Jaomal; Ayesha, Ivonne; Rukhman, Alghif Aruni Nur
Jurnal Ragam Pengabdian Vol. 3 No. 2 (2026): Mei-Agustus, Sustainable Development Goals (SDGs): Multidisciplinary Perspectiv
Publisher : Lembaga Teewan Journal Solutions

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62710/e874v280

Abstract

The adoption of smart farming in horticulture is increasingly important for improving productivity and promoting sustainable agriculture. However, previous studies have mainly focused on the pre-adoption stage, while determinants influencing technology use after adoption remain underexplored. This study aimed to analyze the determinants of smart farming adoption at the post-adoption stage and examine its effects on farm productivity and sustainability. A quantitative explanatory design was employed using survey data from 70 horticultural farmers in West Bandung Regency, Indonesia. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The results revealed that Perceived Usefulness (PU), Observability (OBS), and Image (IMG) positively and significantly influenced the level of smart farming adoption. In contrast, Perceived Ease of Use (PEOU), Relative Advantage (RA), Compatibility (COMP), and Trialability (TRI) showed no significant effects. Moreover, smart farming adoption had positive and significant effects on both farm productivity and farming sustainability. These findings indicate that, at the post-adoption stage, farmers’ actual experiences, perceived benefits, and social recognition play more important roles than the initial characteristics of the innovation. This study extends the Technology Acceptance Model (TAM) and Innovation Diffusion Theory (IDT) by demonstrating that determinants of technology adoption evolve across different stages of technology use, providing implications for policies promoting sustainable digital agriculture.