K-Means Clustering Using Principal Component Analysis (PCA) Indonesia Multi-Finance Industry Performance Before and During Covid-19
- DOI
- 10.21776/ub.apmba.2022.011.02.1
- Published
- 2022-12-31
- Container
- Asia Pacific Management and Business Application
- Publisher
- Brawijaya University
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.21776/ub.apmba.2022.011.02.1,
title = {K-Means Clustering Using Principal Component Analysis (PCA) Indonesia Multi-Finance Industry Performance Before and During Covid-19},
author = {Sri Mulyaningsih and Jerry Heikal},
year = {2022},
journal = {Asia Pacific Management and Business Application},
doi = {10.21776/ub.apmba.2022.011.02.1},
url = {https://doi.org/10.21776/ub.apmba.2022.011.02.1}
}RIS
TY - JOUR TI - K-Means Clustering Using Principal Component Analysis (PCA) Indonesia Multi-Finance Industry Performance Before and During Covid-19 AU - Sri Mulyaningsih AU - Jerry Heikal PY - 2022 JO - Asia Pacific Management and Business Application DO - 10.21776/ub.apmba.2022.011.02.1 UR - https://doi.org/10.21776/ub.apmba.2022.011.02.1 ER -
APA
Mulyaningsih, S., & Heikal, J. (2022). K-Means Clustering Using Principal Component Analysis (PCA) Indonesia Multi-Finance Industry Performance Before and During Covid-19. Asia Pacific Management and Business Application. https://doi.org/10.21776/ub.apmba.2022.011.02.1
Source records
- crossref · retrieved 2026-09-25T20:09:03.963Z