Purwono Purwono

103 total papers · 530 total citations
58 papers, 252 citations indexed

About

Purwono Purwono is a scholar working on Information Systems, Artificial Intelligence and Health Information Management. According to data from OpenAlex, Purwono Purwono has authored 58 papers receiving a total of 252 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Information Systems, 16 papers in Artificial Intelligence and 5 papers in Health Information Management. Recurrent topics in Purwono Purwono's work include Edcuational Technology Systems (12 papers), Blockchain Technology in Education and Learning (9 papers) and Data Mining and Machine Learning Applications (9 papers). Purwono Purwono is often cited by papers focused on Edcuational Technology Systems (12 papers), Blockchain Technology in Education and Learning (9 papers) and Data Mining and Machine Learning Applications (9 papers). Purwono Purwono collaborates with scholars based in Indonesia, Taiwan and Japan. Purwono Purwono's co-authors include Alfian Ma’arif, Wahyu Rahmaniar, Qazi Mazhar ul Haq, Haris Imam Karim Fathurrahman, Imam Riadi, Khoirun Nisa, Rusydi Umar, Windu Gata, Sobir Sobir and Edi Santosa and has published in prestigious journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and Environmental Monitoring and Assessment.

In The Last Decade

Purwono Purwono

43 papers receiving 232 citations

Author Peers

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

Author						Papers	Cites
Purwono Purwono	86	68	23	22	17	58	252
Endah Purwanti	116 1.3×	133 2.0×	22 1.0×	17 0.8×	9 0.5×	72	271
Sukemi Sukemi	64 0.7×	54 0.8×	10 0.4×	20 0.9×	9 0.5×	70	279
Andi Wahju Rahardjo Emanuel	76 0.9×	59 0.9×	29 1.3×	12 0.5×	7 0.4×	73	326
Nur Hayati	52 0.6×	52 0.8×	43 1.9×	32 1.5×	6 0.4×	52	330
Naeem Ahmed Mahoto	63 0.7×	159 2.3×	22 1.0×	7 0.3×	17 1.0×	35	327
Teddy Suparyanto	53 0.6×	40 0.6×	9 0.4×	20 0.9×	26 1.5×	51	293
Noor Azah Samsudin	82 1.0×	160 2.4×	44 1.9×	8 0.4×	8 0.5×	60	312
Umi Salamah	59 0.7×	52 0.8×	44 1.9×	5 0.2×	8 0.5×	66	220
Muhammad Iqbal Hossain	106 1.2×	85 1.3×	36 1.6×	19 0.9×	6 0.4×	58	303
J. Jayanthi	44 0.5×	75 1.1×	45 2.0×	19 0.9×	12 0.7×	62	296

Countries citing papers authored by Purwono Purwono

Since Specialization

Citations

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

Fields of papers citing papers by Purwono Purwono

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Purwono Purwono

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