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Researcher · Universitas Darul Ulum · Indonesia

Lailia Rahmawati

Lailia Rahmawati publishes mostly in Information Systems, Education and Artificial Intelligence, on topics such as Data Mining and Machine Learning Applications, Computer Science and Engineering and Multimedia Learning Systems.

OpenAlex
World rank
#5,607,243
of 7,710,434 ranked researchers
Rank in Indonesia
#56,367
of 148,020
Works
18
Citations
18
Citations per work
1.0
h-index
3
i10-index 0Top 83% in Information Systems
Lailia Rahmawati

What does Lailia Rahmawati research?

Lailia Rahmawati's work is mostly in Computer Science (53%), Social Sciences (16%), Agricultural and Biological Sciences (4%).

Physical Sciences: 10 works · 56.9% of their workComputer Science: 10 works · 53.0% of their workInformation Systems: 5 works · 27.5% of their workArtificial Intelligence: 3 works · 15.7% of their workComputer Vision and Pattern Recognition: 2 works · 9.8% of their workEngineering: 1 works · 3.9% of their workBiomedical Engineering: 1 works · 3.9% of their workEverything else: 4 works · 23.5% of their workSocial Sciences: 3 works · 15.7% of their workSocial Sciences: 3 works · 15.7% of their workEducation: 3 works · 15.7% of their workLife Sciences: 1 works · 3.9% of their workAgricultural and Biological Sciences: 1 works · 3.9% of their workAquatic Science: 1 works · 3.9% of their workTHEIR WORKLailia Rahmawati18works
Life Sciences4%Physical Sciences57%Social Sciences16%

Their six largest subfields, inside their fields and domains; the grey slice is everything else they publish. The interactive view splits every one of their works down to single topics.

The fields and subfields, with their numbers
    1. Computer Science1053.0%
    2. Engineering13.9%
  2. Everything else423.5%
    1. Social Sciences315.7%
    1. Agricultural and Biological Sciences13.9%
  1. 1Information Systems28% of their works
  2. 2Education16% of their works
  3. 3Artificial Intelligence16% of their works
  4. 4Computer Vision and Pattern Recognition10% of their works
  5. 5Biomedical Engineering4% of their works
  6. 6Aquatic Science4% of their works

Research topics

Which keywords describe Lailia Rahmawati's research?

The keywords of their largest research topics: Artificial Intelligence, Data Mining, Machine Learning, E-Learning, Classification Algorithms, Neural Networks, Artificial Neural Networks and Digital Image Processing.

Size is their works in the topics tagged with each word, from their 8 largest topics. Each links to the topic it comes from most. The words come from the keyword list OpenAlex gives each topic, not from the text of the papers, so a word can appear that none of the papers uses.

All 20 words, with their numbers
  1. Artificial Intelligence92 topics
  2. Data Mining92 topics
  3. Machine Learning82 topics
  4. E-Learning72 topics
  5. Classification Algorithms61 topic
  6. Neural Networks61 topic
  7. Artificial Neural Networks51 topic
  8. Digital Image Processing51 topic
  9. Learning51 topic
  10. Multimedia51 topic
  11. Decision Support System31 topic
  12. Expert Systems31 topic
  13. Aquaponics21 topic
  14. Breath Analysis21 topic
  15. Contrast Enhancement21 topic
  16. Dehazing21 topic
  17. Educational Challenges21 topic
  18. Electronic Nose21 topic
  19. Internet of Things21 topic
  20. Sustainability21 topic

Where does Lailia Rahmawati work?

Lailia Rahmawati's main affiliation in the publication record is Universitas Darul Ulum, Indonesia.

How many publications and citations does Lailia Rahmawati have?

OpenAlex counts 18 works and 18 citations for Lailia Rahmawati, an h-index of 3, ranking #5,607,243 of 7,710,434 researchers worldwide on the quality score.

Ranked on field-normalised citation excellence (50%), output (30%) and citations (20%). Counts come from OpenAlex author records, which occasionally merge different people who share a name or split one person into several.

Papers, co-authors, who cited this work and researchers on the nearest topics have tabs of their own, above. Is this your page? Claim it with your ORCID iD, or request a correction or removal.

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