Geospatial Analysis of Nitrogen Efficiency: Correlating Subsidized Urea Distribution with National Rice and Maize Productivity Across Provinces

Abstract

Indonesia’s food security is highly dependent on rice and maize production, for which subsidized urea fertilizer represents the primary source of nitrogen input. However, persistent low Nitrogen Use Efficiency (NUE) raises concerns about allocation effectiveness amid rising subsidy costs and environmental degradation. This study examines the spatial correlation between subsidized urea distribution density (kg/ha) and provincial rice/maize productivity (ton/ha) across Indonesia (2020–2024) to identify oversaturation regions. Official secondary data obtained from BPS and the Ministry of Agriculture were processed to generate density variables and a nitrogen use efficiency (NUE) proxy. Subsequently, the dataset was analyzed using GIS, Global and Local Moran’s I (LISA), and Geographically Weighted Regression (GWR). Results reveal weak global correlations (rice r=0.125; maize r=0.210) but significant spatial non-stationarity, with GWR outperforming OLS (rice R²=0.68 vs. 0.02). LISA identified HL clusters (high urea-low productivity) in Kalimantan, Sumatra, and Java, confirmed by negative/zero GWR coefficients (β₁=-0.15 to 0.42), indicating chronic oversaturation in 8 provinces. These findings demonstrate input-output decoupling beyond nitrogen thresholds, urging geospatial NUE-based subsidy reform: reduce allocations in HL clusters for budget savings, redirect to deficient LL regions, and prioritize soil/irrigation interventions. This approach optimizes yields, cuts fiscal waste, and mitigates N₂O emissions.