Catur Supriyanto

137 total papers · 471 total citations
74 papers, 322 citations indexed

About

Catur Supriyanto is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Catur Supriyanto has authored 74 papers receiving a total of 322 indexed citations (citations by other indexed papers that have themselves been cited), including 42 papers in Artificial Intelligence, 37 papers in Information Systems and 15 papers in Computer Vision and Pattern Recognition. Recurrent topics in Catur Supriyanto's work include Data Mining and Machine Learning Applications (26 papers), Edcuational Technology Systems (13 papers) and Multimedia Learning Systems (12 papers). Catur Supriyanto is often cited by papers focused on Data Mining and Machine Learning Applications (26 papers), Edcuational Technology Systems (13 papers) and Multimedia Learning Systems (12 papers). Catur Supriyanto collaborates with scholars based in Indonesia, Malaysia and Bangladesh. Catur Supriyanto's co-authors include Pulung Nurtantio Andono, Muljono Muljono, Ricardus Anggi Pramunendar, Guruh Fajar Shidik, Abdul Syukur, Edi Noersasongko, Agus Harjoko, Moch Arief Soeleman, Heru Agus Santoso and Purwanto Purwanto and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of King Saud University - Computer and Information Sciences and Journal of Intelligent & Fuzzy Systems.

In The Last Decade

Catur Supriyanto

58 papers receiving 304 citations

Author Peers

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

Author						Papers	Cites
Catur Supriyanto	166	127	79	37	22	74	322
Faisal Dharma Adhinata	92 0.6×	95 0.7×	72 0.9×	10 0.3×	14 0.6×	69	323
Rd. Rohmat Saedudin	123 0.7×	98 0.8×	22 0.3×	16 0.4×	8 0.4×	74	325
Aruna Bhat	115 0.7×	46 0.4×	93 1.2×	25 0.7×	6 0.3×	71	337
Sarah Masud Preum	138 0.8×	39 0.3×	87 1.1×	44 1.2×	9 0.4×	39	323
Isredza Rahmi A. Hamid	119 0.7×	138 1.1×	57 0.7×	65 1.8×	11 0.5×	35	276
Jyoti Agarwal	81 0.5×	55 0.4×	22 0.3×	16 0.4×	12 0.5×	35	246
Zainab Abu Bakar	200 1.2×	93 0.7×	52 0.7×	33 0.9×	9 0.4×	80	348
Ya Zhou	140 0.8×	60 0.5×	81 1.0×	15 0.4×	8 0.4×	57	293
Teng Guo	100 0.6×	34 0.3×	199 2.5×	12 0.3×	17 0.8×	36	350
Edi Noersasongko	178 1.1×	51 0.4×	103 1.3×	41 1.1×	4 0.2×	46	337

Countries citing papers authored by Catur Supriyanto

Since Specialization

Citations

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

Fields of papers citing papers by Catur Supriyanto

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Catur Supriyanto. 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 Catur Supriyanto. The network helps show where Catur Supriyanto may publish in the future.

Co-authorship network of co-authors of Catur Supriyanto

This figure shows the co-authorship network connecting the top 25 collaborators of Catur Supriyanto. A scholar is included among the top collaborators of Catur Supriyanto 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 Catur Supriyanto. Catur Supriyanto 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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