Muhammad Rivai

137 papers receiving 777 citations

Peers

Muhammad Rivai
Comparison fields: 5 of 117
  • Computer Science Applications 140
  • Water Science and Technology 95
  • Biomedical Engineering 269
  • Analytical Chemistry 59
  • Electrical and Electronic Engineering 316
Replace Djoko Purwanto with:
Djoko Purwanto Indonesia
Latifah Munirah Kamarudin Malaysia
Amol P. Bhondekar India
Tamoghna Ojha India
Meo Vincent C. Caya Philippines
Kamran Abid Pakistan
Mohd Amri Md Yunus Malaysia
Achilles D. Boursianis Greece
Jocelyn F. Villaverde Philippines
Muhammad Rivai relative to Djoko Purwanto Indonesia Djoko Purwanto's profile →
Citations per field
00.5×5.2×
Djoko Purwanto · 1×
Citations per year

Countries citing papers authored by Muhammad Rivai

Since Specialization
Citations

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

Fields of papers citing papers by Muhammad Rivai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 21 scholars most cited alongside Muhammad Rivai, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Muhammad Rivai Line = papers co-authored together Muhammad Rivai links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 179 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201649
2 201940
3 201630
4 201829
5 201525
6 201624
7 201924
8 202323
9 201823
10 201820
11 201920
12 202218
13 202017
14 201116
15 201715
16 201715
17 201514
18 201814
19 201714
20 201812

About Muhammad Rivai

Muhammad Rivai is a scholar working on Electrical and Electronic Engineering, Biomedical Engineering, Computer Science Applications, Artificial Intelligence and Water Science and Technology, having authored 179 papers that have together received 948 indexed citations. Recurring topics across this work include Advanced Chemical Sensor Technologies (45 papers), Engineering and Technology Innovations (34 papers), IoT-based Control Systems (28 papers), Gas Sensing Nanomaterials and Sensors (21 papers), Water Quality Monitoring Technologies (17 papers), Computer Science and Engineering (17 papers), Insect Pheromone Research and Control (11 papers) and Multimedia Learning Systems (10 papers). The work is most often cited by research in Computer Science Applications (140 citations), Water Science and Technology (95 citations), Biomedical Engineering (269 citations), Analytical Chemistry (59 citations) and Electrical and Electronic Engineering (316 citations). Muhammad Rivai has collaborated with scholars based in Indonesia and Taiwan. Frequent co-authors include Djoko Purwanto, Suwito Suwito, Mauridhi Hery Purnomo, Achmad Arifin, Shintami Chusnul Hidayati, Riyanarto Sarno, Tri Arief Sardjono, Misbah Misbah, Shanq-Jang Ruan and Ontoseno Penangsang. Their work appears in journals such as IEEE Access, Computers and Electronics in Agriculture, TELKOMNIKA (Telecommunication Computing Electronics and Control), International journal of intelligent engineering and systems and International Journal on Advanced Science Engineering and Information Technology.

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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