<![CDATA[The rapid expansion of built-up land, measured as Impervious Surface Area (ISA), in Pekanbaru City has raised concerns about urban sustainability and regulatory compliance. This study develops a sustainable control model for built-up land growth integrating normative-legal and empirical-spatial perspectives. Using the Spatial Sustainability Assessment Model (SSAM) and GIS, 702,556 raster pixels of spatial data were analyzed, and systematic sampling generated 76 sample points for logistic regression analysis. Sixty-seven independent variables were examined, comprising biophysical (12), social (31), and economic (24) factors. Ensemble machine learning models, particularly CatBoost with GoldenFeatures, were applied to predict ISA growth and identify key drivers, including urban land values, population density, and the location of health and education facilities. Findings indicate that weak enforcement of relevant laws and regional regulations exacerbates unregulated land conversion. The study provides actionable insights for local governments, recommending stricter zoning enforcement, alignment with environmental laws, and targeted monitoring of high-risk areas to achieve sustainable urban growth. It recommends using the model for risk-based monitoring, enabling a shift from reactive penalties to proactive zoning enforcement to achieve sustainable urban growth.]]>
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