Analisis Bibliometrik SDM AI Industri Indonesia Berbasis OpenAlex: Metode CTM - Syahadatul Aditya; Aswin Rosadi (Ikatan Ahli Informatika Indonesia, 2025)
This study maps the research landscape of HR–AI in the Indonesian industry context using OpenAlex open data for the 2015–2025 period (with 2025 being partial). After curation (deduplication, language detection, normalization, and removal of very short documents), the corpus was analyzed using Contextualized Topic Models (CTM) based on multilingual embeddings and compared with a lightweight baseline, Latent Semantic Analysis(LSA). The number of topics was tested at K = 10; K* was determined by the peak of c_v coherence and cross-checked with c_npmi on candidate K values. The results show that CTM consistently outperforms LSA in coherence across the same K range and yields more stable topic labels. A topics-over-time analysis highlights four major thematic clusters—workforce upskilling/reskilling, HR analytics and process automation, AI governance and ethics (including compliance with Indonesia’s Personal Data Protection Law, UU PDP), and the digital transformation of education/curricula—with several topics exhibiting upward trends since 2019. These findings offer practical recommendations for organizations and policymakers: designing analytics-driven competency-building programs, strengthening data and model governance and audits, and integrating curricula aligned with industry needs. All artifacts (processed data, tables, and figures) are provided to support replication and verification.