Meilani, Indri (2024) Analisis Kualitas Publikasi Ilmiah Di Indonesia Dengan Longitudinal Study 2013-2023. Masters thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Penelitian ini bertujuan untuk menganalisis kualitas publikasi di Indonesia selama periode 2013-2023 dengan longitudinal study dan analisis linier berganda terhadap indikator pemeringkatan kinerja penelitian QS WUR. Melalui pendekatan kuantitatif, penelitian ini akan mengumpulkan data publikasi ilmiah dari basis data Scopus dan Scival untuk mengidentifikasi tren pertumbuhan, distribusi publikasi berdasarkan subject area, kualitas jurnal, kolaborasi internasional, dampak publikasi, H-indeks, FWCI serta analisis discountinue jurnal selama sepuluh tahun terakhir. Analisis scientometric, VOSViewer, statistik deskriptif, longitudinal study dan analisis linier berganda akan digunakan untuk mengevaluasi perubahan kualitas publikasi dan mengidentifikasi faktor-faktor yang mempengaruhi indicator penilaian publikasi dalam pemeringkatan perguruan tinggi global seperti QS WUR. Hasil dari penelitian ini diharapkan dapat menganalisis pengaruh berbagai factor publikasi terhadap International Research Network (IRN), Citation per Lecture, dan Sustainability dalam peringkat QS World University Rankings (QS WUR) 2025 menggunakan metode analisis linier berganda. Variabel independen yang dianalisis meliputi kualitas publikasi meliputi Publikasi Jurnal Q1, Publikasi Kolaborasi Internasional, Total Citation, Citations per Paper, Field-Weighted Citation Impact (FWCI), Open Access, Discountinue Total journal article dan topik Sustainable Development Goals (SDGs) 1-16. Dengan demikian dapat memberikan wawasan yang mendalam tentang dinamika kualitas publikasi di Indonesia dan menghasilkan rekomendasi strategis untuk peningkatan kualitas dan produktivitas serta dampak publikasi di masa depan. Hasil penelitian ini menunjukkan bahwa Publikasi Kolaborasi Internasional sangat berpengaruh signifikan terhadap score International Research Network (IRN) di QS WUR.
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This research aims to analyze the quality of publications in Indonesia during the 2013-2023 period with a longitudinal study and multiple linear analysis of QS WUR research performance ranking indicators. Through a quantitative approach, this research will collect scientific publication data from the Scopus and Scival databases to identify growth trends, publication distribution based on the subject area, journal quality, international collaboration, publication impact, H-index, FWCI, and analysis of journal discounting over the last ten years. Scientometric analysis, VOSViewer, descriptive statistics, longitudinal study, and multiple linear analysis will be used to evaluate changes in the quality of publications and identify factors that influence publication assessment indicators in global higher education rankings such as QS WUR. The results of this research are expected to analyze the influence of various publication factors on the International Research Network (IRN), Citations per Lecture, and Sustainability in the 2025 QS World University Rankings (QS WUR) using multiple linear analysis methods. The independent variables analyzed include publication quality including Q1 Journal Publications, International Collaboration Publications, Total Citations, Citations per Paper, Field-Weighted Citation Impact (FWCI), Open Access, Discounting Total journal articles, and Sustainable Development Goals (SDGs) topics 1-16. In this way, it can provide in-depth insight into the dynamics of publication quality in Indonesia and produce strategic recommendations for improving quality and productivity as well as future publications' impact. The results of this study indicate that International Collaborative Publications have a very significant influence on the International Research Network (IRN) score in QS WUR.
| Item Type: | Thesis (Masters) |
|---|---|
| Uncontrolled Keywords: | kualitas publikasi, regresi linier berganda, scientometric, longitudinal study, world class university |
| Subjects: | Q Science > QA Mathematics > QA278.2 Regression Analysis. Logistic regression |
| Divisions: | Interdisciplinary School of Management and Technology (SIMT) > 61101-Master of Technology Management (MMT) |
| Depositing User: | Indri Meilani |
| Date Deposited: | 12 Aug 2024 03:44 |
| Last Modified: | 16 Aug 2024 07:43 |
| URI: | http://repository.its.ac.id/id/eprint/115341 |
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