DOI: https://doi.org/10.14710/j.gauss.14.1.157-168

DETERMINASI INDIKATOR PEMBANGUNAN KESEHATAN MASYARAKAT (IPKM) DI WILAYAH PESISIR MENGGUNAKAN MODEL STRUCTURAL DENGAN SAMPEL KECIL

*Riwi Dyah Pangesti orcid  -  Program Studi Statistika, Fakultas Matematika dan Ilmu Pengetahuan Alam, Universitas Bengkulu, Jl. WR Soepratman, Kandang Limun Kota Bengkulu, 38371, Indonesia
Dyah Setyo Rini orcid scopus  -  Program Studi Statistika, FMIPA, Universitas Bengkulu, Indonesia
Winalia Agwil orcid scopus  -  Program Studi Statistika, FMIPA, Universitas Bengkulu, Indonesia
Septiara Santi Anggriany  -  Program Studi Statistika, FMIPA, Universitas Bengkulu, Indonesia
Muhammad Kevin Rido Ariendra  -  Program Studi Statistika, FMIPA, Universitas Bengkulu, Indonesia
Open Access Copyright 2025 Jurnal Gaussian under http://creativecommons.org/licenses/by-nc-sa/4.0.

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Abstract
Public health in coastal areas is a crucial aspect of a nation's development but faces unique challenges due to geographical, demographic, and environmental factors. This study seeks to analyze the factors influencing the Health Development Index (HDI) in coastal areas using the Structural Equation Modeling (SEM) approach with the Partial Least Square (PLS) method for a small sample. The analyzed variables include Environmental Health, Health Behavior, Health Services, Poverty Status, and the HDI, as well as their influence on Health Status. This study utilizes secondary data from the 2018 Riskesdas report and BPS publications in the southern part of Sumatra. The analysis results show that Environmental Health has a significant effect of -0,45 and Health Behavior has an effect of -0,30 on Health Status. However, Health Services, Poverty Status, and HDI do not show significant effects on Health Status. By gaining a deeper understanding of the determinants of IPKM in coastal areas, this study is expected to contribute to the development of more targeted and effective health policies. The PLS-SEM approach used in this study is also expected to serve as a reference for other researchers in applying structural models to small samples.

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Keywords: Structural Equation Modeling; Partial Least Square; PLS-SEM; Health Development Index
Funding: Universitas Bengkulu

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