Pavement Condition Analysis Using PCI Method and GIS on the Gayam–Sidorejo Road Segments, Kediri - Moch. Syahrul; Fithri Estikhamah; Bagas Aryaseta (AJARCDE (Asian Journal of Applied Research for Community Development and Empowerment), 2026)
Road pavement deterioration significantly reduces service performance, driving comfort, and traffic safety, making accurate pavement condition evaluation essential for effective maintenance planning. This study aimed to assess pavement condition using the Pavement Condition Index (PCI) method and to map the spatial distribution of pavement distress using Geographic Information Systems (GIS) along the Gayam–Sidorejo road segments in Kediri Regency, Indonesia. Data were collected through field surveys by identifying the type, severity, and dimensions of pavement distress in each sample unit. For systematic analysis, the road was divided into nine segments. PCI values were calculated based on deduct value (DV) and corrected deduct value (CDV) procedures. The results showed that the average PCI value was 48.09, indicating poor pavement condition overall. The lowest PCI value was recorded in Segment 6 (36.2), which was categorised as very poor and requiring structural rehabilitation, while the highest PCI value was recorded in Segment 9 (63.0), which was categorised as fair and requiring routine maintenance. GIS-based mapping using ArcGIS effectively visualized the spatial distribution of pavement conditions across the study area. These findings provide useful information for identifying maintenance priorities and supporting more effective pavement management strategies. Contribution to Sustainable Development Goals (SDGs):SDG 8  : Decent Work and Economic GrowthSDG  9 : Industry, Innovation, and InfrastructureSDG 11: Sustainable Cities and Communities