Abstract
Working children have some impacts that befall them. They are hampered by access to education, exploited in working hours and even experience the two impacts at the same time. This research focus on applying and comparing the classification performance of the impact of working children by multinomial logistic discriminant analysis (MLgDA) and classification and regression tree (CART). MLgDA is useful for dealing with cases that do not meet the linearity assumption and suitable for data containing numerical and categorical predictors. CART is not affected by outliers, collinearity and heteroscedasticity among predictors. The data sourced from National Labor Force Survey 2018. All predictors are categorical and characteristics between regions are different. More than half of working children in Indonesia face some impacts, reaching 54.31%. The best classification performance is produced by MLgDA, with an accuracy of 78.73%. MLgDA is superior to CART in almost all measures.
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