Issue |
ITM Web Conf.
Volume 36, 2021
The 16th IMT-GT International Conference on Mathematics, Statistics and their Applications (ICMSA 2020)
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Article Number | 01008 | |
Number of page(s) | 13 | |
Section | Statistics and Data Science | |
DOI | https://doi.org/10.1051/itmconf/20213601008 | |
Published online | 26 January 2021 |
Modeling of child labour exploitation status in Indonesia using multilevel binary logistic regression
1
STIS Polytechnic of Statistics, Jl. Otto Iskandardinata 64 C, East Jakarta, Indonesia
2
Statistics of Tomohon City, Jl. Nimawanua, Tomohon City, Indonesia
* Corresponding author: lizakurnia@stis.ac.id
The Indonesian constitution recognizes guarantees the right of the child to rest and leisure, to engage in play, and recreational activities appropriate to the age of the child so that they should not be working. Employers are also prohibited to employ children. However, many children come to work because of poverty, even though child labour is close to exploitation. Theoretically, individual and contextual factors affect the exploitation status of child labour. This study aims to analyze the variables that influence the exploitation of child labour in Indonesia based on data from the National Socio-Economic Survey (Susenas) in 2018. The random effect test shows that there are differences between regency/municipality so that multilevel binary logistic regression performs better than one level binary logistic regression. More than 80 percent of child labourers are exploited in terms of education and working hours. Variables that significantly influence the exploitation status of child labour at the individual level are gender, the occupation sector of child labour, and the occupation sector of the household head. Meanwhile, poverty rates and mean years of schooling significantly influence the exploitation status of child labour at the regional level.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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