Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Journal of Creative Power and Ambition (JCPA)
Deasy Susana Ratokoni Ndaparoka
Politeknik Negeri Kupang, Indonesia
Economics, Econometrics & Finance

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Mapping the Distribution of Poverty and Happiness Areas in East Nusa Tenggara Using the Small Area Estimation Method Clara Margilina Reinamah; Deasy Susana Ratokoni Ndaparoka; Raden Setyo Budi Suharto
Journal of Creative Power and Ambition (JCPA) Vol. 4 No. 02 (2026): Journal of Creative Power and Ambition (JCPA)
Publisher : CV Edujavare Publishing

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70610/jcpa.2099

Abstract

Poverty and subjective well-being are related but distinct dimensions of human development. This article outlines a small area estimation (SAE) framework for mapping poverty and happiness profiles across regencies and municipalities in East Nusa Tenggara (NTT), Indonesia. The framework adapts the spatial-analysis approach used in earlier poverty-and-happiness research and identifies the data integration required to produce reliable subprovincial estimates. Publicly available Statistics Indonesia (BPS) data show that the poverty rate in NTT was 19.48% in March 2024 and 19.02% in September 2024; it declined further to 18.60% in March 2025 and 17.50% in September 2025. The provincial Happiness Index was 70.31 in 2021. These published indicators provide context but do not, by themselves, support district-level happiness estimates. The source thesis available for this assignment analyses the Special Region of Yogyakarta, not NTT, and the NTT household microdata and fitted SAE outputs needed to map happiness at small-area level were not supplied. Accordingly, this manuscript distinguishes verified contextual statistics from the proposed estimation workflow and does not invent district-level happiness estimates, model coefficients, standard errors, or map classifications. The framework specifies data harmonisation, model fitting, uncertainty assessment, spatial classification, and validation steps required for a complete empirical article.
Co-Authors Raden Setyo Budi Suharto Reinamah, Clara Margilina