Tata Kelola AI dan Akuntabilitas Algoritmik dalam Administrasi Publik: Analisis Bibliometrik

This study maps publication growth, thematic structure, temporal patterns, and collaboration in research on AI governance and algorithmic accountability in public administration. It analyzes 6,088 publications retrieved from Dimensions for 2017-2026 using a structured Boolean query; the bibliographic metadata were exported on 15 September 2026. VOSviewer was used to examine annual publication counts, text-term co-occurrence from titles and abstracts, overlay patterns, and co-authorship among authors, organizations, and countries. For the text map, a threshold of 30 occurrences yielded 483 terms, from which 290 were selected using the 60% most-relevant-terms option and binary counting. The dataset shows the highest publication counts in 2025 and 2026, with 2026 representing a partial year. The text-term map links public administration and the public sector with algorithmic accountability, human oversight, regulation, auditing, privacy, ethics, algorithmic bias, and public trust. The findings portray a multidimensional field connecting technological, legal, institutional, ethical, and societal concerns, while identifying themes that warrant further substantive and empirical study.