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All Journal Interaksi : Jurnal Ilmu Komunikasi Komunikator OKARA: Jurnal Bahasa dan Sastra KAREBA : Jurnal Ilmu Komunikasi MediaKom : Jurnal Ilmiah Ilmu Komunikasi JRK (Jurnal Riset Komunikasi) PRofesi Humas Jurnal ASPIKOM Jambura Agribusiness Journal Jurnal Profetik Kajian Jurnalisme Warta Ikatan Sarjana Komunikasi Indonesia Dialektika: Jurnal Ekonomi dan Ilmu Sosial KOLONI Majority Science Journal Oshada Jurnal Pendidikan Progresif
Andi Subhan Amir, Andi Subhan
Ilmu Komunikasi Fakultas Ilmu Sosial Dan Ilmu Politik, Universitas Hasanuddin
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Civil Engineering, Building, Construction & Architecture Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Environmental Science Health Professions Immunology & microbiology Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Medicine & Pharmacology Public Health Social Sciences Other

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Analisis Bibliometrik Penelitian Kecerdasan Buatan dalam Pendidikan Tinggi dari Era Pra-Generative AI Hingga Kemunculan Chatgpt (2015-2025) Husnul Hatima; Alem Febri Sonni; Andi Subhan Amir
KOLONI Vol. 5 No. 2 (2026): JUNI 2026
Publisher : Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/koloni.v5i2.818

Abstract

The development of Artificial Intelligence (AI) in higher education has grown significantly over the past decade, particularly following the emergence of generative AI technologies such as ChatGPT. This study aims to map the evolution of AI research in higher education from the pre–generative AI era to the emergence of ChatGPT using a bibliometric approach. Data were collected from the Scopus database covering the period 2015–2025 and analyzed using VOSviewer and RStudio with the bibliometrix package. The analysis employed multiple bibliometric techniques, including co-authorship, keyword co-occurrence, citation, co-citation, bibliographic coupling, and descriptive statistical analysis. The results show a substantial and exponential increase in publications, especially after 2020, with a total of 8,340 documents and an annual growth rate of 9.88%. The co-occurrence analysis reveals several major thematic clusters, ranging from technical aspects such as machine learning to pedagogical integration and the emergence of generative AI topics such as ChatGPT. Furthermore, the findings indicate a shift in research focus from technical and system-oriented approaches toward more pedagogical and normative dimensions, including issues of AI ethics and academic integrity. The co-authorship analysis shows that research collaboration remains fragmented, while global contributions are dominated by a limited number of countries. Overall, this study provides a comprehensive overview of the intellectual structure and development of AI research in higher education and highlights future research directions, particularly in interdisciplinary collaboration, ethical AI implementation, and inclusive knowledge development.
Edufarming Communication Strategy for The Diffusion of Smart Farming Innovation: A Qualitative Case Study of SGH Hydroponic Nur Annisa Putri Nazaruddin; Moehammad Iqbal Sultan; Andi Subhan Amir
Jambura Agribusiness Journal VOLUME 7, ISSUE 2, 2026: JANUARY-JUNE
Publisher : Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37046/jaj.v7i2.38587

Abstract

This study analyzes Edufarming as a communication strategy for diffusing AIoT-based smart farming innovation at SGH Hydroponic in Gowa Regency, South Sulawesi, Indonesia. The study employed a qualitative approach with a descriptive single-case study design. Data were collected through semi-structured interviews, participant observation, and documentation. The informants consisted of the founder, co-founder, two technical staff members of SGH Hydroponic, and one participant in the Edufarming program. The researcher also participated directly in the Edufarming program to observe the learning process, interaction patterns, and technology demonstrations. Data were analyzed using an interactive qualitative model consisting of data collection, data condensation, data display, and conclusion drawing. The analysis also applied thematic categorization based on Rogers’ diffusion of innovation attributes and was strengthened through source and methodological triangulation. The findings show that Edufarming functions not only as an agricultural education activity but also as a participatory communication mechanism that connects technology, agribusiness actors, training participants, and market partners within a learning ecosystem. The diffusion process occurs through technology demonstrations, hands-on practice, interpersonal communication, group learning, and direct observation of production outcomes. AIoT-based hydroponics provides relative advantages through production stability, faster harvesting, product consistency, and stronger market trust. Edufarming also improves compatibility, reduces perceived complexity, facilitates trialability, and strengthens observability through visible plant growth, dashboard-based monitoring, and practical learning activities. The study implies that smart farming diffusion requires technological readiness, structured communication, mentoring, digital literacy support, and participatory learning.
Reporting Indonesia’s New E-Cigarette/Tobacco Regulation (PP 28/2024): Public-Health vs Industry Frames Amir, Andi Subhan; Pangkam, Moti; Joohs, Markus; Prastowo, FX Ari Agung
Jurnal Kajian Jurnalisme Vol 9, No 2 (2026): KAJIAN JURNALISME
Publisher : Journalism Study Program, Faculty of Communication Sciences, Universitas Padjadjaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24198/jkj.v9i2.67927

Abstract

Background: Indonesia’s PP 28/2024 reshapes controls on tobacco and e-cigarette products, making news coverage a crucial venue where policy meaning is constructed. Prior research on media framing and health communication indicates competition between public-health frames (risk, youth protection, efficacy) and industry frames (jobs, costs, consumer choice), motivating hypotheses about outlet differences, headline–body congruence, source–frame coupling, and timing shifts. Purpose: To describe the balance of public-health versus industry frames in Indonesian online news on PP 28/2024 and assess headline–body alignment, sourcing patterns, and early temporal trends. Methods: Quantitative content analysis (unit: article) across five major outlets, August 2024–August 2025; codebook for dominant frame, headline frame, tone, source mix, and evidence cues; 15% double-coding planned (target κ ≥ 0.70); χ² with Cramér’s V, McNemar tests, descriptive tables, and a monthly trend line as primary outcomes. Results: A 10-item pilot (five outlets) found industry frames 6/10 (60%) and public-health frames 4/10 (40%); headline–body agreement was 10/10 (100%). Outlet × frame association was χ² = 10.000, p = .075, Cramér’s V = .707. Public-health–framed pieces more often referenced primary law; later coverage tilted toward economic and compliance narratives, consistent with framing theory and efficacy-timing expectations. No adverse events apply. Conclusion: Early coverage shows competitive framing with strong headline integrity but uneven verification of economic claims. Full-sample analysis will test outlet differences and source–frame coupling and inform practice on mirroring legal specifics, balancing sources, and sustaining risk-and-efficacy context. Implications: Newsrooms should strengthen verification by linking rule-based stories to relevant PP 28/2024 provisions, adding minimal context for numerical claims using official data, and diversifying expert sources to support evidence-based public understanding.
AI-Driven public relations in health communication: Evidence from India and Indonesia Pangkam, Moti; Amir, Andi Subhan; Nugraha, Aat Ruchiat
PRofesi Humas Vol 11, No 1 (2026): August 2026
Publisher : Universitas Padjadjaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24198/prh.v11i1.70227

Abstract

Background: The rapid integration of artificial intelligence (AI) into health communication has redefined the way institutions relate to the public; However, existing studies highlight above all the technological and clinical dimensions, leaving a critical gap in understanding AI-driven public relations as a strategic tool that adapts outcomes such as trust and commitment, especially in developing countries. Purpose: This study aims to examine the influence of AI-driven public relations on public trust and engagement in health communication, as well as the mediating role of public trust, using cross-national insights from India and Indonesia. Methods: This study employed a quantitative survey design involving 320 respondents, equally distributed between India and Indonesia. Respondents were selected through purposive sampling based on their experience accessing health-related information through digital platforms involving AI-supported communication features. The pooled cross-national data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). Results: The results demonstrate that AI-powered public relations significantly enhance public trust and public engagement. Public trust also positively influences engagement and serves as the primary mediating mechanism linking AI-driven communication to engagement outcomes. Conclusion: These results demonstrate that the effectiveness of artificial intelligence in health communication is determined not only by its technological sophistication but also by its ability to promote relationships based on the trust of public engagement. Implications: This research expands on public relations theory, integrating AI into the realm of relational communication, highlighting the sensitive contexts of healthcare institutions working in different sociocultural settings and the importance of trust-oriented AI trust strategies.
Co-Authors Aat Ruchiat Nugraha Abu Jafar Md. Shafiul Alam Bhuiyan Ainun Jariyah Yusuf Ali, Aisyah Alif, Insyirah Salsabila Andi Muhammad Fauzi Ramadhan Andi Wirangga LBM Sungkawawo Candra Aeni Dedi Gunawan Saputra Fatty Faiqah FX. Ari Agung Prastowo Hasrullah, Harullah HERU SUBRATA Husnul Hatima Joohs, Markus Judijanto, Loso Karnay, Sudirman Masita Masita Moehammad Iqbal Sultan Muhammad Akbar Muhammad Nadjib Muhtar, St. Murniati Nosakros Arya, Nosakros Nur Annisa Putri Nazaruddin Nurul Ichsani Pangkam, Moti Sonni, Alem Febri Sudirman Karnay Sultan, M. Iqbal Sultan, Moehammad Iqbal Syamsuddin Aziz Trianasari Triansari Trianasari, Triansari Weraman, Pius Yulia Permatasari, Yulia Yumi Abimulyani Zubairi, Ahmad Zuhrotunida, Zuhrotunida