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Open Access

Peer-reviewed

Research Article

A clustering approach to identify multidimensional poverty indicators for the bottom 40 percent group

Mariah Abdul Rahman,

Roles Data curation, Formal analysis, Investigation, Methodology, Software, Visualization, Writing – original draft, Writing – review & editing

Affiliation Center for Artificial Intelligence Technology, Faculty of Information Science & Technology, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia
⨯
Nor Samsiah Sani ,

Roles Conceptualization, Funding acquisition, Project administration, Resources, Supervision, Validation, Writing – review & editing

* E-mail: norsamsiahsani@ukm.edu.my

Affiliation Center for Artificial Intelligence Technology, Faculty of Information Science & Technology, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia

https://orcid.org/0000-0001-5802-5946

⨯
Rusnita Hamdan,

Roles Data curation, Formal analysis, Methodology, Validation

Affiliation Center for Artificial Intelligence Technology, Faculty of Information Science & Technology, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia
⨯
Zulaiha Ali Othman,

Roles Supervision, Validation, Writing – review & editing

Affiliation Center for Artificial Intelligence Technology, Faculty of Information Science & Technology, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia
⨯
Azuraliza Abu Bakar

Roles Supervision, Validation, Writing – review & editing

Affiliation Center for Artificial Intelligence Technology, Faculty of Information Science & Technology, Universiti Kebangsaan Malaysia, Bangi, Selangor, Malaysia
⨯

A clustering approach to identify multidimensional poverty indicators for the bottom 40 percent group

Mariah Abdul Rahman,
Nor Samsiah Sani,
Rusnita Hamdan,
Zulaiha Ali Othman,
Azuraliza Abu Bakar

x

Published: August 2, 2021
https://doi.org/10.1371/journal.pone.0255312

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