Mitigating gender bias in STEM study field classification using GRU and LSTM with augmented dataset technique
- DOI
- 10.11591/ijict.v15i2.pp447-455
- Published
- 2026-06-01
- Container
- International Journal of Informatics and Communication Technology (IJ-ICT)
- Publisher
- Institute of Advanced Engineering and Science
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.11591/ijict.v15i2.pp447-455,
title = {Mitigating gender bias in STEM study field classification using GRU and LSTM with augmented dataset technique},
author = {Devi Fitrianah and Sarah Safitri and Nadzla Andrita Intan Ghayatrie},
year = {2026},
journal = {International Journal of Informatics and Communication Technology (IJ-ICT)},
doi = {10.11591/ijict.v15i2.pp447-455},
url = {https://doi.org/10.11591/ijict.v15i2.pp447-455}
}RIS
TY - JOUR TI - Mitigating gender bias in STEM study field classification using GRU and LSTM with augmented dataset technique AU - Devi Fitrianah AU - Sarah Safitri AU - Nadzla Andrita Intan Ghayatrie PY - 2026 JO - International Journal of Informatics and Communication Technology (IJ-ICT) DO - 10.11591/ijict.v15i2.pp447-455 UR - https://doi.org/10.11591/ijict.v15i2.pp447-455 ER -
APA
Fitrianah, D., Safitri, S., & Ghayatrie, N. A. I. (2026). Mitigating gender bias in STEM study field classification using GRU and LSTM with augmented dataset technique. International Journal of Informatics and Communication Technology (IJ-ICT). https://doi.org/10.11591/ijict.v15i2.pp447-455
Source records
- crossref · retrieved 2026-09-26T05:45:32.601Z