Rahmad Mahendra
- Artificial Intelligence top 5%
- Information Systems top 5%
- Sociology and Political Science
- Language and Linguistics top 10%
- Computer Vision and Pattern Recognition
- Co-authors
- Mirna AdrianiIndra BudiHendra ManurungSamuel CahyawijayaGenta Indra WinataTimothy BaldwinI Wayan ArkaAde Romadhony
- Topics
- Topic Modeling (21 papers)Natural Language Processing Techniques (18 papers)Sentiment Analysis and Opinion Mining (13 papers)
In The Last Decade
Rahmad Mahendra
42 papers receiving 388 citations
Peers
Comparison fields: 5 of 59
- Artificial Intelligence 322
- Information Systems 140
- Sociology and Political Science 33
- Language and Linguistics 27
- Computer Vision and Pattern Recognition 23
Countries citing papers authored by Rahmad Mahendra
This map shows the geographic impact of Rahmad Mahendra'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 Rahmad Mahendra with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rahmad Mahendra more than expected).
Fields of papers citing papers by Rahmad Mahendra
This network shows the impact of papers produced by Rahmad Mahendra. 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 Rahmad Mahendra. The network helps show where Rahmad Mahendra may publish in the future.
Co-authorship network of co-authors of Rahmad Mahendra
This figure shows the co-authorship network connecting the top 25 collaborators of Rahmad Mahendra. A scholar is included among the top collaborators of Rahmad Mahendra 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 Rahmad Mahendra. Rahmad Mahendra 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 | 3 | |
| 3 | 1 | |
| 4 | 25 | |
| 5 | 45 | |
| 6 | 2 | |
| 7 | 2 | |
| 8 | 7 | |
| 9 | The Framework of Multiword Expression in Indonesian Language | 2 |
| 10 | 28 | |
| 11 | 1 | |
| 12 | 4 | |
| 13 | 2 | |
| 14 | 11 | |
| 15 | 3 | |
| 16 | 2 | |
| 17 | Anterior maxillary tooth proportions and the golden percentage concept in the deutero-malay race (study on dental students in the faculty of dentistry, universitas indonesia) | 4 |
| 18 | 0 | |
| 19 | 1 | |
| 20 | Extending an Indonesian Semantic Analysis-based Question Answering System with Linguistic and World Knowledge Axioms | 8 |
About Rahmad Mahendra
Rahmad Mahendra is a scholar working on Artificial Intelligence, Information Systems and General Social Sciences, having authored 45 papers that have together received 418 indexed citations. Recurring topics across this work include Topic Modeling (21 papers), Natural Language Processing Techniques (18 papers) and Sentiment Analysis and Opinion Mining (13 papers). The work is most often cited by research in Artificial Intelligence (322 citations), Information Systems (140 citations) and Transportation (21 citations). Rahmad Mahendra has collaborated with scholars based in Indonesia, Australia and Hong Kong. Frequent co-authors include Mirna Adriani, Indra Budi, Hendra Manurung, Samuel Cahyawijaya, Genta Indra Winata, Timothy Baldwin, I Wayan Arka, Ade Romadhony, Alham Fikri Aji and Jey Han Lau. Their work appears in journals such as Journal Of Big Data, Transactions of the Association for Computational Linguistics and Big Data and Cognitive Computing.
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.