Purpose: This study aims to examine the effect of smart farming implementation on food crop productivity in Indonesia and analyze the moderating role of climate change on this relationship.

Research Methodology: This study used a quantitative cross-sectional survey design conducted among food crop farmers in Indonesia. Data were collected using a structured questionnaire with a five-point Likert scale. Purposive sampling was applied to 200 respondents. The analysis was performed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS software to test reliability, validity, and hypothesis relationships.

Results: The findings show that the implementation of smart farming positively influences crop productivity. Climate change significantly affects crop productivity. Furthermore, climate change strengthens the relationship between smart farming and crop productivity.

Conclusions: Write the main conclusions of the research. Smart farming plays an important role in improving food crop productivity, especially under increasing climate-change pressures.

Limitations: This study relied on self-reported survey data and used a cross-sectional design, limiting long-term causal interpretation.

Contributions: This study contributes to digital agriculture and climate adaptation research by providing empirical evidence of the role of smart farming in improving productivity and resilience, supporting policymakers and farmers in developing climate-smart agricultural strategies.