Aplikasi Bayesian Networks dalam Evaluasi Tingkat Adopsi Irigasi Tetes
Application of Bayesian Networks for Evaluating the Adoption Rate of Drip Irrigation
DOI:
https://doi.org/10.29244/jp2wd.2025.9.3.%25pKeywords:
adoption, bayesian networks, drip irrigation, innovation, technologyAbstract
Limited resources, particularly land and water, are considered one of the main challenges in increasing Indonesia's food production. One way to address this is through the use of drip irrigation. Despite its many advantages and widespread use around the world, the adoption rate of drip irrigation in Indonesia remains low. This study aims to explore the issue of adoption by examining Banyuwangi Regency as a case study. Farmers in Banyuwangi Regency were interviewed to understand the factors influencing their adoption of drip irrigation, followed by a diffusion process analysis using a Bayesian Network. The interviews revealed that only 12 out of 92 farmer respondents had adopted drip irrigation. Bayesian Network modeling estimated the probability of adoption at 13.78%. Sensitivity analysis indicated that farmers' financial capacity, the perceived lucrativeness of the technology, and limited access to the technology were among the major factors contributing to the low adoption rate.
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