JSTAR
Vol 5 No 2 (2025): Jurnal Statistika Terapan

ANALISIS KEMISKINAN RUMAH TANGGA SEKTOR INFORMAL DI PROVINSI NUSA TENGGARA TIMUR TAHUN 2024

Maria Kewa (Badan Pusat Statistik Kabupaten Lembata)
Yulianus Ronaldias (Badan Pusat Statistik Kabupaten Lembata)



Article Info

Publish Date
31 Dec 2025

Abstract

Households whose heads work in the informal sector tend to be more vulnerable to poverty. The informal sector plays a significant role in providing employment opportunities; however, jobs in this sector are generally unstable, low-paying, and lack social protection. These conditions make households engaged in the informal sector more likely to be trapped in the cycle of poverty. This study aims to analyze the factors influencing the poverty status of households whose heads work in the informal sector in East Nusa Tenggara (NTT). The results of the binary logistic regression model estimation indicate that the variables significantly affecting the poverty status of informal-sector households in NTT include the classification of residential area, number of household members, age of the household head, highest educational attainment of the household head, main employment sector, number of working hours per week, internet access, ownership of a savings account, and ownership of household assets. Based on these findings, the government needs to accelerate the expansion of social protection programs such as employment insurance, health insurance, and social assistance. Access to financing should also be made easier. In addition, comprehensive policies in the agricultural sector must be implemented, including maintaining price stability, ensuring market access, and empowering farmers.

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Journal Info

Abbrev

JSTAR

Publisher

Subject

Humanities Computer Science & IT Economics, Econometrics & Finance Social Sciences

Description

Aim: JSTAR studies applied statistics at the regional and national levels of East Nusa Tenggara which are directed to contribute to the government in making regional development policies. JSTAR pays special attention to official and modeling statistics, big data and data mining, and the application ...