Digital Competency Assessment of Farmer Groups: A Training Needs Analysis for Agricultural Digital Transformation in West Java - Ikhsan Nendi; Amelia Amelia (Equivalent: Jurnal Ilmiah Sosial Teknik, 2026)
Background: Agriculture 4.0 is reshaping farming worldwide, yet Indonesian farmer groups remain constrained by uneven digital competency. National census data show that 53.16 percent of the 28.19 million farmers in Indonesia still work without modern machinery or digital technology. Objective: This study measures the digital competency level of farmer group members, ranks their priority training needs by domain, and tests the individual factors that shape those needs. Methods: A cross sectional survey covered 210 members of 21 farmer groups in Indramayu, Subang, and Karawang, West Java, drawn by stratified random sampling. The instrument was adapted from DigComp 2.1 and validated by five experts. Analysis was run in SPSS 26 using descriptive statistics, gap analysis, the Training Priority Index, Importance-Performance Analysis, and multiple linear regression after classical assumption testing. Results: Mean current competency reached 56.4 of 100 against a required standard of 80.0, a gap of 23.6 points. The widest gaps were digital agricultural applications (29.4), digital marketing (27.1), and precision farming technology (25.8). Education level (β = 0.412), digital infrastructure access (β = 0.376), and age (β = −0.318) significantly predicted competency and explained 42.8 percent of its variance. Conclusion: Training for farmer groups should be differentiated rather than uniform, pairing foundational digital literacy for older and less educated members with advanced application and marketing modules for younger members who can act as digital champions. Extension agencies can use the Training Priority Index reported here to sequence modules and to schedule training alongside rural connectivity investment.