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I'm Married too Young: How To Pursue Legal Marriage? Yusnissa, Hertina; Nooraeni, Rani; Lestariningsih, Eni
Jurnal Ekonomi Kependudukan dan Keluarga
Publisher : UI Scholars Hub

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Abstract

One of the social problems in West Nusa Tenggara Province, Indonesia is high rates of under-registered child marriage. Marriage registration is an obligation in marriage legislation in Indonesia and also an issue of human rights. Studies on marriage registration are very limited in Indonesia. Therefore, this study aims to examine the critical determinants that affect the provision of having a marriage certificate in case of child marriage in West Nusa Tenggara, Indonesia. The study used the 2022 Indonesia National Socio-Economic Survey (SUSENAS) data. The analysis was done using descriptive statistics and binary logistic regression. The results indicate that the variables included in the analysis are statistically significant. The odds ratio indicates that women are more likely to register their marriage than men. It is more likely that people who lived in the urban areas, people who married after 16 years, people who had been educated in senior high school and above, people who were employed, and people who accessed the internet/social media were more likely to register their marriage. People who had not joined Bank Accounts, who came from rich families, and who had social insurance from the government were in line with those who did not register their marriage (odd ratio=1). The finding in this study concluded that gender, age at marriage, place of residence, wealth index, education, working status, joint bank account, media exposure, and receiving social insurance from the government are the leading determinants of registered child marriage in West Nusa Tenggara, Indonesia. Furthermore, there is a need to educate the importance of registering a marriage to society more intensively and the policy makers should campaign awareness of existing marriage certificates.
Pendekatan Competing Risks dalam Menganalisis Kembali Bekerjanya Pekerja White-Collar Pasca COVID-19: Pembelajaran dari Indonesia Christoffel, Joseph; Hutagaol, Octavia Rogate; Uluwiyah, Ana; Lestariningsih, Eni
Jurnal Ketenagakerjaan Vol 20 No 2 (2025)
Publisher : Pusat Pengembangan Kebijakan Ketenagakerjaan Kementerian Ketenagakerjaan Republik Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47198/jnaker.v20i2.584

Abstract

Despite the recovery trend in the labor market after the scarring effects caused by the pandemic, the share of white-collar workers remains below pre-pandemic levels. This study aims to analyze the determinants of reemployment among individuals who exited the workforce due to COVID-19, with a specific focus on differences between white-collar and blue-collar workers. We use micro data from the August 2022 National Labor Force Survey (Sakernas) and employ a survival analysis with the Fine and Gray competing risks model to estimate the subdistribution hazard ration (SHR) for each covariate such as gender, living area, education, and age. The results show that individuals living in urban areas, with post-secondary education, younger age (15–30 years), previous white-collar work experience, and participation in training programs have a significantly higher likelihood of reemployment in white-collar occupations. Conversely, blue-collar reemployment is more likely among those with lower education, rural residence, head-of-household status, previous blue-collar work experience and unmarried individuals. This research emphasizes the importance of investing in human capital and post secondary education for maximizing white-collar jobs reabsorption.
Small Area Estimation of Extreme Poverty Using Zero-Inflated Binomial GLMM: A District-Level Case Study in North Sumatra 2024 Lumban Gaol, Marta Desna Fitria Br.; Iryani, Beta Septi; Lestariningsih, Eni
Proceedings of The International Conference on Data Science and Official Statistics Vol. 2025 No. 1 (2025): Proceedings of 2025 International Conference on Data Science and Official St
Publisher : Politeknik Statistika STIS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34123/icdsos.v2025i1.714

Abstract

Eradicating extreme poverty is a key objective of Sustainable Development Goal (SDG) 1, with a global benchmark of reducing the proportion of people living below the US$1.90 PPP poverty line. However, in 2024, Indonesia—particularly North Sumatra Province—continues to face persistent challenges in achieving this target. Direct estimation based on the Foster-Greer-Thorbecke (FGT) formula using SUSENAS microdata suffers from large sampling errors (RSE > 25 percent) and zero estimates in multiple districts due to small or absent samples, indicating serious issues of zero inflation and overdispersion. To overcome these limitations, this study applies a model-based Small Area Estimation (SAE) approach using the Zero-Inflated Binomial Generalized Linear Mixed Model (ZIB-GLMM). This method incorporates auxiliary variables from the 2024 PODES dataset and effectively addresses the dual complexities of excess zeros and inter-district variability. Simulation results show that ZIB-GLMM outperforms conventional SAE models in terms of predictive accuracy and model stability. The proposed method offers realistic and policy-relevant district-level estimates of extreme poverty, providing robust evidence to inform targeted interventions and strengthen Indonesia’s national agenda to eradicate extreme poverty.