Information Quality Drives Taxpayer Compliance in the Coretax Administration System

General Background: Digital tax administration has become central to modernizing public financial services and supporting taxpayer compliance. Specific Background: Indonesia's Coretax Administration System (CTAS) integrates taxation services, although technical constraints and varying user readiness present challenges during implementation. Knowledge Gap: Existing studies have primarily examined system quality, information quality, and user satisfaction, while evidence concerning their relationships with taxpayer compliance in the Coretax context remains limited, particularly in Palembang. Aims: This study examines the relationships between system quality, information quality, and taxpayer compliance using the DeLone and McLean Information Systems Success Model. A quantitative survey involving 100 Coretax users in Palembang was conducted, and the data were analyzed through multiple linear regression using SPSS. Results: System quality demonstrated a positive but statistically insignificant relationship with taxpayer compliance (t = 1.099; p = 0.275). Conversely, information quality showed a positive and significant relationship (t = 4.963; p < 0.001). Both variables were jointly significant in explaining taxpayer compliance (F = 14.938; p < 0.001). Novelty: The findings distinguish the statistical contributions of technical system characteristics and information quality to compliance within Indonesia's newly implemented digital tax administration platform. Implications: Tax administrators should prioritize information accuracy, completeness, consistency, and timely updates while maintaining reliable system functionality and accessible user assistance to support tax compliance. Highlights: Technical system characteristics showed no statistically significant individual association (p = 0.275). Accurate and relevant information demonstrated a significant positive relationship (p < 0.001). Both predictors were jointly significant in the regression model (F = 14.938).