Quality Evaluation on Higher Education Research Articles Publication using Artificial Intelligence Dedy Kurniadi- Rahmat Gernowo- Bayu Surarso
Doktor Sistem Informasi, Universitas Diponegoro
Abstract
Evaluating the quality of research article publications from universities is essential, given the sharp increase in international article publications. This quality assessment is a complex and critical process in the world of higher education to identify universities contributing to global-level research. One primary aspect of assessing university quality based on international publication output is the quantity of scholarly publications produced by the university. Universities that are actively engaged in research and produce numerous publications tend to have a greater contribution. However, it^s important to note that a high quantity of publications does not necessarily guarantee high publication quality.
Data for this research was collected from the Scopus database using the Application Programming Interface (API). To determine publication quality, a journal rank database was constructed using Integration Scimago Journal Rank data. The research utilized the Promethee II algorithm to identify the best alternatives among Indonesian universities, ranking them based on the quality of their international publications.
The results of this research yielded an integrated system with Scopus and Scimago Journal Rank databases, ranking the top 25 universities in Indonesia. From the research, a total of 326,000 indexed articles from these 25 universities were obtained. Subsequently, Promethee II ranking was applied, resulting in the University of Indonesia securing the top position with a net flow value of 0.85. Following that, the University of Diponegoro ranked second with a net flow value of 0.15. The third position was held by Binus University with a net flow value of -0.0158267 among the 25 universities in Indonesia.
Keywords: Quality Systems, API, Artificial Intelligence, Net Flow, Rank
