Improving Motor Vehicle Tax Payment Services at the UPTB in the Gowa Samsat Area through the SAMKEPO Program: JEL Classification: H21, H83, H71, O33, D73, R58 - Taufikurrahman Taufikurrahman; Muliyadi Hamid; Abdul Samad Arief (Journal of Management and Administration Provision, 2026)
This study analyzes the effectiveness of the Remote Mobile Samsat (SAMKEPO) program in improving motor vehicle tax payment services at the UPTB Samsat Gowa, South Sulawesi. SAMKEPO was developed to address low taxpayer compliance in remote areas due to geographical barriers, limited accessibility, and inadequate service quality in conventional systems. Using a qualitative approach, data were collected through in-depth interviews, participant observation, document analysis, and literature review involving taxpayers, Samsat officers, and policymakers. Findings show that SAMKEPO significantly improved service coverage up by 40% and increased taxpayer compliance by 25–35%. The program reduced average service time from 2–3 hours to 15–30 minutes, lowered arrears by 35%, and enhanced public satisfaction by 90% among users. Key success factors include adequate infrastructure and logistics, skilled and empathetic human resources, community engagement through local leaders, and alignment of service schedules with socio-economic activities. Technology integration, such as real-time database access and on-site digital payments, increased transparency and efficiency, while collaborative governance between agencies strengthened operational synergy. However, challenges remain in digital literacy, network connectivity, and service expansion to more remote districts. The study recommends optimizing the SAMSAT mobile application with accessible features, strengthening digital literacy programs, and enhancing inter-agency collaboration to ensure sustainable improvement. SAMKEPO demonstrates that integrating technology, mobility, and community-based approaches can modernize public tax services, foster compliance, and contribute to regional revenue growth, making it a replicable model for other regions in Indonesia.