Bens Pardamean

4.4k total citations
304 papers, 2.5k citations indexed

About

Bens Pardamean is a scholar working on Artificial Intelligence, Information Systems and Molecular Biology. According to data from OpenAlex, Bens Pardamean has authored 304 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 55 papers in Artificial Intelligence, 47 papers in Information Systems and 32 papers in Molecular Biology. Recurrent topics in Bens Pardamean's work include Oil Palm Production and Sustainability (15 papers), Technology Adoption and User Behaviour (13 papers) and COVID-19 diagnosis using AI (12 papers). Bens Pardamean is often cited by papers focused on Oil Palm Production and Sustainability (15 papers), Technology Adoption and User Behaviour (13 papers) and COVID-19 diagnosis using AI (12 papers). Bens Pardamean collaborates with scholars based in Indonesia, Taiwan and United States. Bens Pardamean's co-authors include Tjeng Wawan Cenggoro, Arif Budiarto, Rezzy Eko Caraka, Reza Rahutomo, Alam Ahmad Hidayat, Teddy Suparyanto, Anzaludin Samsinga Perbangsa, Prana Ugiana Gio, Bharuno Mahesworo and James W. Baurley and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and Journal of the American Geriatrics Society.

In The Last Decade

Bens Pardamean

255 papers receiving 2.4k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Bens Pardamean Indonesia 26 441 309 266 212 204 304 2.5k
Lan Umek Slovenia 16 297 0.7× 467 1.5× 145 0.5× 236 1.1× 53 0.3× 43 3.1k
Peng Yu China 32 634 1.4× 286 0.9× 138 0.5× 424 2.0× 431 2.1× 468 4.7k
Anita Gehlot India 30 527 1.2× 565 1.8× 173 0.7× 116 0.5× 209 1.0× 331 3.7k
Suyanto Suyanto Indonesia 23 763 1.7× 259 0.8× 119 0.4× 195 0.9× 161 0.8× 277 2.1k
Adnan Abid Pakistan 24 621 1.4× 582 1.9× 531 2.0× 78 0.4× 253 1.2× 104 2.6k
Karim Rejeb Tunisia 30 291 0.7× 759 2.5× 325 1.2× 348 1.6× 154 0.8× 71 3.3k
Michael Hahsler United States 19 591 1.3× 422 1.4× 115 0.4× 112 0.5× 206 1.0× 79 2.4k
Youngjo Lee South Korea 29 383 0.9× 72 0.2× 155 0.6× 390 1.8× 49 0.2× 192 3.6k
Kamran Shaukat Australia 33 1.3k 3.0× 644 2.1× 138 0.5× 136 0.6× 411 2.0× 74 3.2k
Hossein Ahmadi Iran 27 608 1.4× 318 1.0× 58 0.2× 256 1.2× 149 0.7× 88 2.7k

Countries citing papers authored by Bens Pardamean

Since Specialization
Citations

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

Fields of papers citing papers by Bens Pardamean

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bens Pardamean

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

All Works

20 of 20 papers shown
1.
Caraka, Rezzy Eko, et al.. (2025). Understanding financial trends through LPS publications using big data topic modeling: a Shariah and conventional finance perspective. Journal of Islamic accounting and business research. 1–40.
2.
Elwirehardja, Gregorius Natanael, et al.. (2025). Depression detection through transformers-based emotion recognition in multivariate time series facial data. IAES International Journal of Artificial Intelligence. 14(2). 1302–1302.
3.
Henry, Mélissa, et al.. (2024). LDA Topic Modeling for Bioinformatics Terms in arXiv Documents. Procedia Computer Science. 245. 229–238. 1 indexed citations
4.
Suparyanto, Teddy, et al.. (2024). Seed Dormancy Breaking and Germination Rate Improvement in Mucuna (Mucuna bracteata) Seeds using Mechanical and Fungicide Treatments. SHILAP Revista de lepidopterología. 94. 6002–6002.
5.
Suparyanto, Teddy, et al.. (2024). Jejak.in as digital platform for vegetation analysis and estimation of carbon stock in KEHATI aqua park. AIP conference proceedings. 3026. 50010–50010.
7.
Caraka, Rezzy Eko, Robert Kurniawan, Prana Ugiana Gio, et al.. (2024). Understanding Pediatric Health Trends in Papua: Insights From SUSENAS, RISKESDAS, Remote Sensing, and Its Relevance to Prabowo and Gibran’s Free Lunch and Milk Program. IEEE Access. 12. 51536–51555. 4 indexed citations
8.
Suparyanto, Teddy, et al.. (2023). Trunk injection fertilization to enhance average bunch weight of palm oil for sustainable water management. IOP Conference Series Earth and Environmental Science. 1183(1). 12045–12045. 2 indexed citations
9.
Harito, Christian, Gregorius Natanael Elwirehardja, Bens Pardamean, et al.. (2023). Battery optimization by machine learning algorithms: Research gap via bibliometric analysis. SHILAP Revista de lepidopterología. 388. 1020–1020. 6 indexed citations
10.
Suparyanto, Teddy, et al.. (2023). Light intensity effect on number of seedlings and growth of Gyrinops versteegii. IOP Conference Series Earth and Environmental Science. 1183(1). 12046–12046. 2 indexed citations
11.
Toharudin, Toni, et al.. (2021). Indonesia in facing new normal: An evidence hybrid forecasting of covid-19 cases using mlp, nnar and elm. Engineering letters. 29(2). 3 indexed citations
12.
Herman, Herman, et al.. (2020). Oil Palm Fruit Image Ripeness Classification with Computer Vision using Deep Learning and Visual Attention. Journal of Telecommunication Electronic and Computer Engineering (JTEC). 12(2). 21–27. 21 indexed citations
13.
Gio, Prana Ugiana, et al.. (2018). Financial Data Statistics Programs. 333–337.
14.
Pardamean, Bens, et al.. (2016). Changing Colorectal Cancer Trends in Asians : Role of Genetic Predisposition, Lifestyle Factors, and Screening(SCOPUS). International Journal of Colorectal Disease. 1(1). 1–2. 1 indexed citations
15.
Perbangsa, Anzaludin Samsinga, et al.. (2015). Online Learning Content and Learning Management System for Early Detection of Cervical Cancer. International Journal of Digital Content Technology and its Applications. 9(1). 54–63. 3 indexed citations
16.
Pardamean, Bens, et al.. (2014). 3-D INTERFACE DESIGN OF THE VIRTUAL WORLD IN E-LEARNING. Journal of Theoretical and Applied Information Technology. 62(3). 1–11. 6 indexed citations
17.
Pardamean, Bens, et al.. (2014). Nutrition Management and Diet Monitoring Information System. Research Journal of Applied Sciences. 9(7). 412–417. 3 indexed citations
18.
Pardamean, Bens & Teddy Suparyanto. (2014). A Systematic Approach to Improving E-Learning Implementations in High Schools.. ˜The œturkish online journal of educational technology. 13(3). 19–26. 10 indexed citations
19.
Pardamean, Bens, et al.. (2011). Nutrition management system at a consumer electronics manufacturer. Computational intelligence. 150–154.
20.
Pardamean, Bens, et al.. (1994). The Influence of Computer Training Platform on Subsequent Computer Preferences. Journal of Computing in Teacher Education. 11(2). 19–25.

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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