Universitas Saburai

About

In recent decades, authors affiliated with Universitas Saburai have published 265 papers, which have received a total of 694 indexed citations. Scholars at this organization have produced 108 papers in Information Systems, 62 papers in Artificial Intelligence and 51 papers in Education on the topics of Edcuational Technology Systems (44 papers), Data Mining and Machine Learning Applications (38 papers) and Multimedia Learning Systems (30 papers). Their work is cited by papers focused on Information Systems (232 citations), Artificial Intelligence (150 citations) and Education (133 citations). Authors at Universitas Saburai collaborate with scholars in Indonesia, United States and Malaysia and have published in prestigious journals including SHILAP Revista de lepidopterología, Hypertension and International Journal of Energy Research. Some of Universitas Saburai's most productive authors include Anthony Anggrawan, Hairani Hairani, Daniele Cusi, Cristina Barlassina, Marco DʼAmico, Marc Maillard, Paolo Manunta, Laura Buzzi, Giuseppe Bianchi and Michel Burnier.

In The Last Decade

Universitas Saburai

162 papers receiving 675 citations

Fields of papers published by authors at Universitas Saburai

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers affiliated with Universitas Saburai at the time of their publication. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers affiliated with Universitas Saburai at the time of their publication.

Countries citing scholars working at Universitas Saburai

Since Specialization

Citations

This map shows the geographic impact of research produced by authors working at Universitas Saburai. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by papers produced at Universitas Saburai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Universitas Saburai more than expected).

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar’s output or impact.

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