Yusra Fernando

41 total papers · 604 total citations
35 papers, 338 citations indexed

About

Yusra Fernando is a scholar working on Information Systems, Artificial Intelligence and Management Information Systems. According to data from OpenAlex, Yusra Fernando has authored 35 papers receiving a total of 338 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Information Systems, 18 papers in Artificial Intelligence and 4 papers in Management Information Systems. Recurrent topics in Yusra Fernando's work include Edcuational Technology Systems (16 papers), Multimedia Learning Systems (16 papers) and Blockchain Technology in Education and Learning (12 papers). Yusra Fernando is often cited by papers focused on Edcuational Technology Systems (16 papers), Multimedia Learning Systems (16 papers) and Blockchain Technology in Education and Learning (12 papers). Yusra Fernando collaborates with scholars based in Indonesia and India. Yusra Fernando's co-authors include Rohmat Indra Borman, Dyah Ayu Megawaty, Debby Alita, Heni Sulistiani, Adi Sucipto, Yuri Rahmanto, Imam Ahmad, Donaya Pasha, Indra Gunawan and Purwono Prasetyawan and has published in prestigious journals such as SHILAP Revista de lepidopterología, Jurnal Nasional Teknologi dan Sistem Informasi and Engineering Technology & Applied Science Research.

In The Last Decade

Yusra Fernando

29 papers receiving 290 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Yusra Fernando	252	192	84	26	22	35	338
Qadhli Jafar Adrian	260 1.0×	176 0.9×	98 1.2×	13 0.5×	37 1.7×	28	369
Styawati Styawati	206 0.8×	139 0.7×	51 0.6×	15 0.6×	14 0.6×	33	299
Indah Fitri Astuti	237 0.9×	166 0.9×	90 1.1×	20 0.8×	35 1.6×	67	330
Joan Angelina Widians	217 0.9×	155 0.8×	59 0.7×	39 1.5×	21 1.0×	59	329
Awang Harsa Kridalaksana	207 0.8×	142 0.7×	56 0.7×	17 0.7×	34 1.5×	50	375
Sari Widya Sihwi	219 0.9×	178 0.9×	47 0.6×	7 0.3×	30 1.4×	42	380
Ade Surahman	263 1.0×	136 0.7×	70 0.8×	14 0.5×	31 1.4×	40	340
I Putu Agus Eka Pratama	225 0.9×	125 0.7×	95 1.1×	38 1.5×	11 0.5×	72	328
Adi Supriyatna	267 1.1×	155 0.8×	65 0.8×	31 1.2×	35 1.6×	34	364
Irawan Afrianto	211 0.8×	111 0.6×	29 0.3×	22 0.8×	39 1.8×	54	301

Countries citing papers authored by Yusra Fernando

Since Specialization

Citations

This map shows the geographic impact of Yusra Fernando's research. 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 Yusra Fernando with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yusra Fernando more than expected).

Fields of papers citing papers by Yusra Fernando

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yusra Fernando. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Yusra Fernando. The network helps show where Yusra Fernando may publish in the future.

Co-authorship network of co-authors of Yusra Fernando

This figure shows the co-authorship network connecting the top 25 collaborators of Yusra Fernando. A scholar is included among the top collaborators of Yusra Fernando based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Yusra Fernando. Yusra Fernando is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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