Every child has human rights to grow and develop as a whole, both physically and mentally. The government prohibits employers from employing children to protect children's rights. In reality, children begin to participate in economic activities as workers. The issue of child labor is very close to exploitation. This research aims to find general facts about exploitation on child laborers and to identify variables that influence exploitation on child laborers in Indonesia in 2018. Data of National Social and Economic Survey (Susenas) in 2018 were analyed through binary logistic regression. The result shows that most of child laborers in 2018 are exploited. Provinces with the highest percentage of child laborers exploitation are DKI Jakarta, Banten, and Central Java. Area of residence, child labor sector, gender of child, and education of household head in the category of junior high school, elementary school, or not graduate from school significantly influence the exploitation of child labor. Child laborers who live in urban areas, male, work in the formal sector, and has a household head who graduate from junior high school or elementary school or doesn’t graduate at all are more likely experience exploitation.
Education gives children the opportunity to have a better life in the future, but unfavorable economic conditions forced children to work and caused some children not to go to school. Child laborers are vulnerable to exploitation because they are considered weak and have no bargaining position in the work world. This study aims to analyze the variables that affect the exploitation of child labor in terms of education. Child laborers are said to be exploited in terms of education if they have never attended school or are no longer in school. The results of the Susenas 2019 show that exploitation is more common in boys, being older, working in the formal sector, working longer hours, living in a rural area, having a smaller household size, having a male, married, not working, low education, and older age household head. The random effect test shows that the variation in the exploitation of child labor in terms of education is significant between groups so that the 3-level model is better than the 1-level binary logistic regression model. The exploitation of child labor in terms of education at the individual level is influenced by age, sector of work, and working hours of children; at the household level it is influenced by the gender and education of household head, classification of residence, level of welfare; and at the regional level it is affected by regency/municipality poverty.
Anak berhak menerima perlindungan dan pemenuhan kebutuhan fisik maupun rohani, namun terdapat anak yang terpaksa bekerja dan menjadikan anak rawan tereksploitasi. Persentase pekerja anak yang tereksploitasi dari sisi jam kerja terus mengalami peningkatan dari tahun 2018 hingga tahun 2020. Sektor informal adalah sektor yang paling banyak dipilih pekerja anak, akan tetapi sektor informal tidak memiliki kontrak dan perlindungan sosial sehingga memperbesar peluang pekerja anak mengalami eksploitasi. Penelitian ini bertujuan untuk mengetahui gambaran umum, variabel yang berpengaruh serta kecenderungan eksploitasi pekerja anak sektor informal dari sisi jam kerja di Indonesia. Data Susenas 2021 dianalisis menggunakan regresi logistik biner. Klasifikasi wilayah tempat tinggal, umur kepala rumah tangga (KRT), pendidikan KRT, dan jenis kelamin anak signifikan memengaruhi eksploitasi pada pekerja anak sektor informal dari sisi jam kerja.
Unemployment is one of the economic problems faced by many countries. In Indonesia, the total workforce has reached 128.06 million and 7.04 million people are unemployed. The indicator to measure unemployment is open unemployment rate (TPT). Java Island becomes the island with the highest TPT, which is 4.04 million people, equivalent to 63.08 percent. The regions that have high TPT rates tend to be in the western region of Java, while the eastern region of Java is moderate. This is an initial allegation of regional influence so spatial analysis needs to be carried out. On the other hand, not many studies have included territorial effects. This study aims to spatially identify the influence of human development index (IPM), labor force particapation rate (TPAK), minimum wage and the dependency ratio on the number of TPT in Java in 2017 with the geographically weighted regression (GWR) method. The results of this study indicate that there are differences in the influence of IPM, TPAK, minimum wage and the dependency ratio on TPT in each area in Java. The most significant independent variables and have a positive relationship are minimum wage. This research also shows that GWR is suitable to be applied in modeling the number of TPT regencies /cities in Java Island in 2017. The results of this study can be used by the government in determining the right policy by looking at regional aspects in overcoming unemployment.
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.
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