Ryan Randy Suryono

1.4k total citations · 1 hit paper
70 papers, 781 citations indexed

About

Ryan Randy Suryono is a scholar working on Information Systems, Management Information Systems and Artificial Intelligence. According to data from OpenAlex, Ryan Randy Suryono has authored 70 papers receiving a total of 781 indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Information Systems, 15 papers in Management Information Systems and 14 papers in Artificial Intelligence. Recurrent topics in Ryan Randy Suryono's work include Information Retrieval and Data Mining (9 papers), Technology Adoption and User Behaviour (9 papers) and Multimedia Learning Systems (8 papers). Ryan Randy Suryono is often cited by papers focused on Information Retrieval and Data Mining (9 papers), Technology Adoption and User Behaviour (9 papers) and Multimedia Learning Systems (8 papers). Ryan Randy Suryono collaborates with scholars based in Indonesia, Italy and Australia. Ryan Randy Suryono's co-authors include Indra Budi, Betty Purwandari, Dana Indra Sensuse, Kautsarina Kautsarina, Dedi Darwis, Achmad Nizar Hidayanto, Ade Dwi Putra, Bayu Anggorojati, Apol Pribadi Subriadi and Ahmad Ari Aldino and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and Heliyon.

In The Last Decade

Ryan Randy Suryono

55 papers receiving 721 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Challenges and Trends of Financial Technology (Fintech): A Systematic Literature Review

2020 203 citations Ryan Randy Suryono, Indra Budi et al. profile →

Peers

Ryan Randy Suryono

MIS

IS

EE

SPS

AI

Mahmood Ali Bahrain

Meyliana Meyliana Indonesia

Haliyana Khalid Malaysia

Narcisa Roxana Moşteanu Malta

Stanislav Mamonov United States

Wassan Abdullah Alkhowaiter Saudi Arabia

Taqwa Hariguna Indonesia

Carla Wilkin Australia

Carol Hsu China

Tero Vartiainen Finland

Mahmood Ali Bahrain

Ryan Randy Suryono

314 ×0.9

MIS

136 ×0.5

IS

212 ×1.4

EE

161 ×1.1

SPS

60 ×0.5

AI

Citations per year, relative to Ryan Randy Suryono Ryan Randy Suryono (= 1×) peers Mahmood Ali

Countries citing papers authored by Ryan Randy Suryono

Since Specialization

Citations

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

Fields of papers citing papers by Ryan Randy Suryono

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ryan Randy Suryono. 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 Ryan Randy Suryono. The network helps show where Ryan Randy Suryono may publish in the future.

Co-authorship network of co-authors of Ryan Randy Suryono

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

All Works

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20 of 20 papers shown

1.

Gunawan, Rudiyanto, et al.. (2025). Modification of Additive Ratio Assessment Method through Distance-Based Weighting Approach for Optimizing Assessment Accuracy. Paradigma - Jurnal Komputer dan Informatika. 27(2). 55–64.

2.

Aldino, Ahmad Ari, et al.. (2025). Advances in Digital Marketing in the Era of Artificial Intelligence. Internet Reference Services Quarterly. 29(2). 245–247. 2 indexed citations

3.

Suryono, Ryan Randy, et al.. (2024). KOMPARASI ALGORITMA SUPPORT VECTOR MACHINE DAN RANDOM FOREST UNTUK ANALISIS SENTIMEN METAVERSE. 7(1). 31–39. 1 indexed citations

4.

Sensuse, Dana Indra, et al.. (2024). The role of data governance in a high-level approach of data migration to open data. Business Information Review. 41(3). 94–103. 2 indexed citations

5.

Suryono, Ryan Randy, et al.. (2024). Analisis Sentimen Publik Terhadap Pengungsi Rohingya di Indonesia dengan Metode Support Vector Machine dan Naïve Bayes. JURNAL MEDIA INFORMATIKA BUDIDARMA. 8(2). 748–748. 3 indexed citations

6.

Santoso, Harry Budi, et al.. (2024). Role, Methodology, and Measurement of Cognitive Load in Computer Science and Information Systems Research. IEEE Access. 12. 190007–190024. 4 indexed citations

7.

Suryono, Ryan Randy, et al.. (2024). Analisis Sentimen Ibu Kota Nusantara menggunakan Algoritma Support Vector Machine dan Naïve Bayes. EDUMATIC Jurnal Pendidikan Informatika. 8(1). 183–192. 1 indexed citations

8.

Hidayanto, Achmad Nizar, et al.. (2023). Sentiment Analysis of Cryptocurrency Trading Platform Service Quality on Playstore Data: A Case of Indodax. SHILAP Revista de lepidopterología. 7(3). 445–456. 2 indexed citations

9.

Suryono, Ryan Randy, et al.. (2023). KLASTERISASI DATA PENJUALAN BERDASARKAN WILAYAH MENGGUNAKAN METODE K-MEANS PADA PT XYZ. 11(2). 157–168. 1 indexed citations

10.

Budi, Indra, et al.. (2023). Twitter dataset on public sentiments towards biodiversity policy in Indonesia. Data in Brief. 52. 109890–109890. 7 indexed citations

11.

Putra, Panca O. Hadi, et al.. (2023). The Integrated Information System Implementation Strategy in Korlantas Polri Based on the Zachman Framework Approach. SHILAP Revista de lepidopterología. 7(2). 381–388. 2 indexed citations

12.

Budi, Indra, et al.. (2023). Purchase Intention and Sentiment Analysis on Twitter Related to Social Commerce. International Journal of Advanced Computer Science and Applications. 14(7). 4 indexed citations

13.

Sensuse, Dana Indra, et al.. (2022). EVALUATION OF DISTANCE LEARNING SYSTEM (E-LEARNING): A SYSTEMATIC LITERATURE REVIEW. 16(1). 132–132. 37 indexed citations

14.

Sensuse, Dana Indra, et al.. (2022). Information Security Risk Assessment (ISRA): A Systematic Literature Review. SHILAP Revista de lepidopterología. 8(2). 207–217.

15.

Suryono, Ryan Randy, et al.. (2021). Why do People Continue using the Webinar Application? Insight in the New Normal Period. 1. 154–161. 1 indexed citations

16.

Suryono, Ryan Randy, et al.. (2020). AUDIT TATA KELOLA TEKNOLOGI INFORMASI MENGGUNAKAN KERANGKA KERJA COBIT 5 PADA DINAS PEKERJAAN UMUM KABUPATEN TANGGAMUS. 1(1). 39–46. 9 indexed citations

17.

Suryono, Ryan Randy. (2019). FINANCIAL TECHNOLOGY (FINTECH) IN AXIOLOGY PERSPECTIVE.

18.

Suryono, Ryan Randy, et al.. (2017). Rancangan Arsitektur Sistem Berbasis Pengetahuan Obat Buatan untuk Kebutuhan Swamedikasi. 3(1). 231–234. 1 indexed citations

19.

Suryono, Ryan Randy, et al.. (2010). ANALISA PERUBAHAN MANAJEMEN DALAM IMPLEMENTASI SI/TI PADA PERGURUAN TINGGI ABC. Seminar Nasional Aplikasi Teknologi Informasi (SNATI). 8 indexed citations

20.

Putra, Ade Dwi, et al.. (2009). Rancang Bangun Media Pembelajaran TOEFL Berbasis Web. Seminar Nasional Aplikasi Teknologi Informasi (SNATI). 129927. 9 indexed citations

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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