Utomo Pujianto

85 total papers · 824 total citations
67 papers, 517 citations indexed

About

Utomo Pujianto is a scholar working on Information Systems, Artificial Intelligence and Health Information Management. According to data from OpenAlex, Utomo Pujianto has authored 67 papers receiving a total of 517 indexed citations (citations by other indexed papers that have themselves been cited), including 51 papers in Information Systems, 40 papers in Artificial Intelligence and 11 papers in Health Information Management. Recurrent topics in Utomo Pujianto's work include Data Mining and Machine Learning Applications (34 papers), Edcuational Technology Systems (29 papers) and Information Retrieval and Data Mining (13 papers). Utomo Pujianto is often cited by papers focused on Data Mining and Machine Learning Applications (34 papers), Edcuational Technology Systems (29 papers) and Information Retrieval and Data Mining (13 papers). Utomo Pujianto collaborates with scholars based in Indonesia, Australia and Türkiye. Utomo Pujianto's co-authors include Aji Prasetya Wibawa, Agung Bella Putra Utama, Muladi Muladi, Hakkun Elmunsyah, Felix Andika Dwiyanto, Triyanna Widiyaningtyas, Andrew Nafalski, Ilham Ari Elbaith Zaeni, Hiroshi Okumura and Didik Dwi Prasetya and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal Of Big Data and Journal of Physics Conference Series.

In The Last Decade

Utomo Pujianto

60 papers receiving 485 citations

Author Peers

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

Author						Papers	Cites
Utomo Pujianto	216	183	61	54	49	67	517
Mukesh Kumar	167 0.8×	130 0.7×	111 1.8×	71 1.3×	48 1.0×	54	571
Abdul Rahim Ahmad	195 0.9×	142 0.8×	129 2.1×	24 0.4×	79 1.6×	65	576
Samina Kausar	200 0.9×	87 0.5×	58 1.0×	32 0.6×	41 0.8×	59	555
Isma Farah Siddiqui	156 0.7×	160 0.9×	48 0.8×	32 0.6×	101 2.1×	44	481
Shuzlina Abdul-Rahman	160 0.7×	100 0.5×	48 0.8×	45 0.8×	41 0.8×	91	583
Vikram Bali	132 0.6×	117 0.6×	53 0.9×	27 0.5×	107 2.2×	59	529
Alaa Khalaf Hamoud	164 0.8×	126 0.7×	225 3.7×	80 1.5×	42 0.9×	37	515
Nawal Sael	246 1.1×	132 0.7×	45 0.7×	9 0.2×	52 1.1×	62	528
Andreas Prinz	88 0.4×	147 0.8×	15 0.2×	46 0.9×	27 0.6×	76	568
Faouzia Benabbou	295 1.4×	142 0.8×	33 0.5×	10 0.2×	38 0.8×	60	553

Countries citing papers authored by Utomo Pujianto

Since Specialization

Citations

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

Fields of papers citing papers by Utomo Pujianto

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Utomo Pujianto

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