Isman Kurniawan

582 citations
88 papers · 377 indexed · h-index 10
Topics
Computational Drug Discovery Methods (27 papers)Machine Learning in Bioinformatics (12 papers)Diverse Scientific Research Studies (9 papers)
Journals
SHILAP Revista de lepidopterologíaChemosphereIEEE Access
Partner nations
IndonesiaMalaysiaJapan

In The Last Decade

Isman Kurniawan

62 papers receiving 372 citations

Peers

Isman Kurniawan
Comparison fields: 5 of 98
  • Molecular Biology 121
  • Computational Theory and Mathematics 97
  • Renewable Energy, Sustainability and the Environment 53
  • Artificial Intelligence 43
  • Organic Chemistry 33
Replace Latifa Khaouane with:
Latifa Khaouane Algeria
Ismail A. Elhaty Türkiye
Cherif Si‐Moussa Algeria
Enrique J. Herrera-López Mexico
Lili Chen China
Muslem Muslem Indonesia
Yitian Fang China
Junnan Zhao China
M. Asadollahi-Baboli Iran
Isman Kurniawan relative to Latifa Khaouane Algeria Latifa Khaouane's profile →
Citations per field
00.5×2.9×
Latifa Khaouane · 1×
Citations per year

Countries citing papers authored by Isman Kurniawan

Since Specialization
Citations

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

Fields of papers citing papers by Isman Kurniawan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Isman Kurniawan

This figure shows the co-authorship network connecting the top 25 collaborators of Isman Kurniawan. A scholar is included among the top collaborators of Isman Kurniawan 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 Isman Kurniawan. Isman Kurniawan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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Analisis Perbandingan Pembobotan TF-IDF dan TF-RF pada Trending Topic di Twitter dengan Menggunakan Klasifikasi K-Nearest Neighbor
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Analisis Trending Topik Pada Twitter Menggunakan Metode Naive Bayes Dengan Pembobotan Tf-idf
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About Isman Kurniawan

Isman Kurniawan is a scholar working on Computational Theory and Mathematics, Health Information Management and Artificial Intelligence, having authored 88 papers that have together received 377 indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (27 papers), Machine Learning in Bioinformatics (12 papers) and Diverse Scientific Research Studies (9 papers). The work is most often cited by research in Computational Theory and Mathematics (97 citations), Renewable Energy, Sustainability and the Environment (53 citations) and Applied Microbiology and Biotechnology (5 citations). Isman Kurniawan has collaborated with scholars based in Indonesia, Malaysia and Japan. Frequent co-authors include Kemas Muslim Lhaksmana, Erwin Budi Setiawan, Apurav Krishna Koyande, Asri Peni Wulandari, Heli Siti Halimatul Munawaroh, Andriati Ningrum, Pau Loke Show, Fhira Nhita, Hauwa Mohammed Mustafa and Rahmat Hidayat. Their work appears in journals such as SHILAP Revista de lepidopterología, Chemosphere and IEEE Access.

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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