Muhamad Handar
Indonesia Open University

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

Community-Based AI Pedagogical Literacy: A Case Study of AI Adoption in Teacher Professional Communities Muhamad Handar; Shani Ramadhan Rasyid; Nur Indah Kumala
Jogjakarta Communication Conference (JCC) Vol. 4 No. 1 (2026): The 7th Jogjakarta Communication Conference (JCC)
Publisher : Jogjakarta Communication Conference (JCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The rapid development of artificial intelligence (AI), particularly generative AI technologies, has transformed the educational communication ecosystem and reshaped how knowledge is produced, distributed, and interpreted in learning environments. In the context, teachers play important roles not only as users of technology but also as mediators of knowledge and facilitators of pedagogical communication in digitally mediated classrooms. Although research on AI literacy in education continues to grow, many studies emphasize students’ competencies or institutional technology adoption, while limited attention has been given to how teachers collectively interpret and adopt AI within professional learning communities. To position this study within the existing research landscape, a bibliometric analysis using Publish or Perish and VOSviewer was conducted with the keywords “community-bases learning” and “digital literacy teachers.” The mapping highlights the central role of community interaction in connecting teachers’ digital literacy development with pedagogical practices. This study adopts a qualitative case study approach focusing on members of the Persatuan Guru Nahdlatul Ulama (Pergunu) in Bekasi City who participated as beneficiaries in the “AI Ready” AI literacy initiative. Data were collected through in-depth interviews, focus group-discussion, and documentation of training activities. The study examines how teachers interpret, negotiate, and collaboratively integrate AI tools into teaching practices, highlighting the role of professional communities in foresting meaningful AI adoption in education.
Digital Civic Engagement and Policy Misinformation: Hoax Narratives of Indonesia’s Free Nutritious Meal Program Muhamad Handar; Lidwina Hana; Purbowo Purbowo
Jogjakarta Communication Conference (JCC) Vol. 4 No. 1 (2026): The 7th Jogjakarta Communication Conference (JCC)
Publisher : Jogjakarta Communication Conference (JCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The rapid expansion of digital media ecosystem has accelerated the circulation of misinformation surrounding public policies. In Indonesia, one policy that has recently become the subject of online misinformation is the Free Nutritious Meal Program (Program Makan Bergizi Gratis/MBG), a national initiative aimed at improving children’s nutritious and strengthening human capital development. While existing studies on misinformation largely focus on political elections and health crises, limited research has examined misinformation narratives related to welfare and food policy. This study analyzes the characteristics and framing of hoax narratives related to the Free Nutritious Meal Program and explores their implication for digital civic engagement. The research employs a qualitative approach using qualitative content analysis and framing analysis. Data were collected from fact-checking archive of TurnBackHoax, managed by the Indonesian Antihoax Society (Mafindo). Using the keyword “makan bergizi gratis,” the dataset consists of 30 verified hoax cases published between 2024 and 2026. The analysis examines narrative structures, content typologies, and dissemination patterns of misinformation across digital platforms. This research contributes to the study of policy misinformation by highlighting how hoax narratives shape public perceptions of food policy and proposes a policy-based hoax literacy approach to strengthen digital civic engagement and public information resillience.