<![CDATA[Community service activities conducted in Kediri City demonstrated that spatial regression models effectively explain traffic variations at major intersections. The analysis showed that vehicle speed and volume are significantly influenced by intersection location, arm direction, and vehicle type. High R-square values, reaching 83% at Semampir Intersection and 82% at Bandar Alim Intersection, indicate that quantitative and spatial approaches accurately describe traffic conditions. These findings suggest that traffic planning and control should be tailored to the characteristics of each intersection. The program also included outreach, technical training, and group discussions with the Kediri City Transportation Agency, enabling participants to interpret regression outputs, including T-tests, ANOVA, and spatial maps, and apply them to technical policies. The activities produced data-driven recommendations, including adaptive traffic signal timing, restrictions on heavy vehicles during peak hours, and the development of a real-time traffic monitoring system, with Semampir and Bandar Alim as pilot intersections.]]>
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