<![CDATA[This research investigates the impact of Weather Prediction, Resource Management, and Land Optimization on the adoption of Big Data Analytics in agricultural land utilization within the agrarian region of West Java. Employing a quantitative approach, the study integrates measurement model analysis, structural equation modeling, demographic profiling, and model fit assessment to comprehensively explore the intricate dynamics of technological adoption in agriculture. Results indicate that Land Optimization, Resource Management, and Weather Prediction significantly influence the adoption of Big Data Analytics. Demographic factors such as gender, age, education, and farming experience demonstrate varying correlations with key variables. The model exhibits strong fit, and approximately 60.2% of the variance in Big Data Analytics adoption is explained by the combined influence of the identified factors. This study contributes nuanced insights to inform policy and practice for sustainable and technology-driven agriculture in West Java.]]>
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