MYRESEARCHMAP: AN ARTIFICIAL INTELLIGENCE-BASED SYSTEM FOR STUDENT RESEARCH MAPPING THROUGH THE INTEGRATION OF BIBLIOMETRIC ANALYSIS AND CHATGPT

Authors

  • Nur Hasyim Latif Universitas Muhammadiyah Yogyakarta, Indonesia
  • Aidilla Qurotianti aidilla.qurotianti@umy.ac.id
  • Muhammad Erdiansyah Cholid Anjali Universitas Muhammadiyah Yogyakarta, Indonesia
  • Riani Khusna Ari Shandy Universitas Muhammadiyah Yogyakarta, Indonesia
  • Bima Ridho Pratama Universitas Muhammadiyah Yogyakarta, Indonesia

DOI:

https://doi.org/10.21154/pustakaloka.v18i1.13383

Abstract

The achievement of the vision and mission of study programs in higher education is closely associated with the quality of students' research. However, many students struggle to identify current, relevant research topics aligned with institutional strategic priorities, resulting in repetitive, saturated themes. This study develops and evaluates MYResearchMap, an Artificial Intelligence (AI)-based student research mapping system that integrates bibliometric analysis and ChatGPT to map research trends and generate research topic recommendations aligned with the vision and mission of study programs. The study employed a mixed methods approach combining quantitative and qualitative techniques. Data were obtained from the metadata of students' scholarly works stored in the institutional repository, including titles, keywords, abstracts, and publication years, while students, lecturers, and librarians participated in the system evaluation. The research process comprised metadata collection, data cleaning, bibliometric analysis, exporting results in JSON format, integrating bibliometric analysis with ChatGPT to generate research recommendations, and visualizing the findings on the library website. The results demonstrate that MYResearchMap effectively maps student research trends, identifies both dominant and underexplored research topics, analyzes the alignment of research with the vision and mission of study programs, and generates more relevant research topic recommendations. Based on the survey, 97% of respondents reported that MYResearchMap helped them identify new research ideas, more than 90% considered the research trend mapping and topic distribution features beneficial, and all respondents agreed that the system was relevant to the vision and mission of their study programs. These findings indicate that MYResearchMap enhances research literacy and supports data-driven academic decision-making through research trend mapping and research topic recommendations aligned with the vision and mission of study programs.

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Published

2026-07-17

Issue

Vol. 18 No. 1 (2026): Pustakaloka

Section

Articles

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