Imam Much Ibnu Subroto
- Information Systems top 5%
- Artificial Intelligence top 10%
- Computer Networks and Communications top 10%
- Sociology and Political Science
- Health Information Management top 5%
- Co-authors
- Tole SutiknoDeris StiawanLina HandayaniMunawar Agus RiyadiMoloud AbdarGoli ArjiSharareh Rostam Niakan KalhoriAli Selamat
- Topics
- Edcuational Technology Systems (12 papers)Multimedia Learning Systems (7 papers)Decision Support System Applications (6 papers)
- Journals
- IEEE AccessJournal of King Saud University - Computer and Information SciencesSocial Network Analysis and Mining
- Partner nations
- IndonesiaMalaysiaSaudi Arabia
In The Last Decade
Imam Much Ibnu Subroto
37 papers receiving 414 citations
Peers
Comparison fields: 5 of 100
- Information Systems 171
- Artificial Intelligence 156
- Computer Networks and Communications 77
- Sociology and Political Science 53
- Health Information Management 52
Countries citing papers authored by Imam Much Ibnu Subroto
This map shows the geographic impact of Imam Much Ibnu Subroto'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 Imam Much Ibnu Subroto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Imam Much Ibnu Subroto more than expected).
Fields of papers citing papers by Imam Much Ibnu Subroto
This network shows the impact of papers produced by Imam Much Ibnu Subroto. 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 Imam Much Ibnu Subroto. The network helps show where Imam Much Ibnu Subroto may publish in the future.
Co-authorship network of co-authors of Imam Much Ibnu Subroto
This figure shows the co-authorship network connecting the top 25 collaborators of Imam Much Ibnu Subroto. A scholar is included among the top collaborators of Imam Much Ibnu Subroto 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 Imam Much Ibnu Subroto. Imam Much Ibnu Subroto is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 0 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 2 | |
| 7 | 11 | |
| 8 | 29 | |
| 9 | Indonesian Articles Recommender System Using n-gram and Tanimoto Coefficient | 3 |
| 10 | 4 | |
| 11 | 2 | |
| 12 | 2 | |
| 13 | 1 | |
| 14 | 5 | |
| 15 | 75 | |
| 16 | 8 | |
| 17 | 3 | |
| 18 | 11 | |
| 19 | 2 | |
| 20 | 4 |
About Imam Much Ibnu Subroto
Imam Much Ibnu Subroto is a scholar working on Information Systems, Management Information Systems and Artificial Intelligence, having authored 42 papers that have together received 450 indexed citations. Recurring topics across this work include Edcuational Technology Systems (12 papers), Multimedia Learning Systems (7 papers) and Decision Support System Applications (6 papers). The work is most often cited by research in Health Information Management (52 citations), Information Systems (171 citations) and Artificial Intelligence (156 citations). Imam Much Ibnu Subroto has collaborated with scholars based in Indonesia, Malaysia and Saudi Arabia. Frequent co-authors include Tole Sutikno, Deris Stiawan, Lina Handayani, Munawar Agus Riyadi, Moloud Abdar, Goli Arji, Sharareh Rostam Niakan Kalhori, Ali Selamat, Rahmat Budiarto and Mohd. Yazid Idris. Their work appears in journals such as IEEE Access, Journal of King Saud University - Computer and Information Sciences and Social Network Analysis and Mining.
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.