Main Article Content
Abstract
This study aims to examine and analyze the socio-demographic, socio-economic, and regional characteristics that influence an individual on being Not in Employment, Education, or Training (NEET). The data is from the February 2018 National Labor Force Survey (Sakernas) and analysed using binary logistic regression with descriptive and inferential approach. The descriptive results show that socio-demographic characteristics such as female, married, and having disability tend to become NEET. Socio-economic characteristics such as graduating from high school and living with an employed household head also tend to become NEET. Furthermore, regional characteristics such as living in rural area and living in area outside Java Island tend to become an NEET. Meanwhile, the inferential results show that female, married, having disability, not graduating from school, living with an unemployed household head, living in rural area, and living in Java Island have significant effect on the chances of becoming NEET
