Panel Data Model Selection and Significant Determinants of New Family Planning Participants in West Sumatra

Authors

  • Diah Triwulandari Universitas Negeri Padang
  • Fadhilah Fitri Universitas Negeri Padang

DOI:

https://doi.org/10.24036/ujsds/vol3-iss3/404

Keywords:

Family Planning, Panel Regression, Random Effect Model, West Sumatra

Abstract

Population issues in Indonesia are not limited to poverty, urbanization, population explosion, or high birth rates, but also include how small families can improve and maintain their quality of life. The main objective of the Family Planning program is to create happy and prosperous families with an ideal number of children. The West Sumatra Provincial Health Office report (2023) emphasizes that increasing the number of new family planning acceptors is an important priority to support the success of maternal, child, and family planning health programs, in line with the 2020–2024 RPJMN policy direction. Therefore, this study aims to develop the best panel data model and identify the factors that significantly influence the number of new family planning participants in West Sumatra Province. The secondary data used were obtained from the Statistics Indonesia (BPS) publication entitled West Sumatra Province in Figures from 2021 to 2024. The observation units in this study were 19 districts/cities in West Sumatra Province with a time series from 2020 to 2023. The results indicate that the best-selected model is the random effect model, with the number of couples of reproductive age proven to have a significant effect on the number of new family planning participants. The R-square value of 53.11% indicates that the model can explain 53.11% of the variation in the dependent variable, while the remaining 46.89% is influenced by other factors not included in the model.

 

Published

2025-08-30

How to Cite

Diah Triwulandari, & Fadhilah Fitri. (2025). Panel Data Model Selection and Significant Determinants of New Family Planning Participants in West Sumatra. UNP Journal of Statistics and Data Science, 3(3), 263–270. https://doi.org/10.24036/ujsds/vol3-iss3/404

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