Analisis Model Struktural Perilaku Penggunaan Aplikasi Pertanian Digital dalam Peningkatan Produktivitas Petani Padi di Provinsi Jawa Timur

Setyabudi, Ibnu Fajar (2025) Analisis Model Struktural Perilaku Penggunaan Aplikasi Pertanian Digital dalam Peningkatan Produktivitas Petani Padi di Provinsi Jawa Timur. Masters thesis, Politeknik Negeri Jember.

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Abstract

This study was motivated by the suboptimal use of digital technology among farmers despite the availability of various digital farming applications. The research aimed to analyze the influence of farmer characteristics, the role of agricultural extension workers, and local leaders on digital farming application use behaviour and its impact on rice farmers’ productivity in East Java Province. A quantitative explanatory approach with a survey method was employed involving 258 farmers as a sample of digital farming application users. Samples were selected through multistage sampling in three regencies implementing digital farming programs on rice commodity, namely Trenggalek, Jember, and Banyuwangi. Data were analyzed using Structural Equation Modeling–Partial Least Squares (SEM-PLS) to examine direct and indirect relationships among variables. The results showed that farmer characteristics, the role of agricultural extension workers, and local leaders had positive and significant effects on digital farming application use behaviour. However, farmer characteristics and the role of extension workers did not directly and significantly affect rice farmers’ productivity, while the role of local leaders showed weak significance. Digital farming application use behaviour had a positive and significant effect on productivity and acted as an important mediating variable. These findings indicate that improving rice productivity is more effectively achieved by strengthening farmers’ behaviour in using digital technology. The research model demonstrated good fit and predictive capability. The implications of this research emphasize strengthening digital farming application use behaviour, enhancing the capacity of local leaders as social learning agents, and developing more integrated digital farming application systems.

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