Model Prioritisasi Pengawasan Maladministrasi Pelayanan Publik: Integrasi Laporan Pengaduan dan Big Data Analytics

Public service oversight in Indonesia has gained increasing urgency in response to growing societal demands for transparency, accountability, and participatory governance. Although the regulatory framework—anchored by Law No. 25 of 2009 and Law No. 37 of 2008—provides a foundational mandate, the prioritization of complaints remains hindered by resource constraints and the absence of a real-time, evidence-based mechanism. This gap between public expectations and institutional capacity underscores the need for a more strategic approach to complaint management. The present study aims to map key issues in public service complaints by comparing two analytical approaches: manual analysis of data from the Ombudsman of the Republic of Indonesia and big data-driven insights generated through Intelligence Media Analytics (IMA). Employing a descriptive-exploratory method grounded in literature review, the research juxtaposes findings from the Ombudsman’s Annual Report with IMA outputs. The results reveal four dominant areas of concern—land affairs, civil service, education, and law enforcement—consistently identified across both methodologies. This convergence highlights the potential of big data as a critical tool for prioritizing oversight efforts in a timely and evidence-informed manner. Ultimately, the integration of traditional and digital analytics may enhance the effectiveness and efficiency of maladministration monitoring in Indonesia’s public service landscape.