Identifying Characteristics of Households Recipient of the Government’s Social Protection Program

Abstract

According to Statistics Indonesia, the number of poor people increased by 1,12 million people in March 2020. In March 2021, the percentage of poor people increased by 0,36 points compared to March 2020. The percentage of poor people in Banten Province has increased in the last three years (2019-2021). One way to reduce poverty by the government is to increase social protection programs. The characteristics of households receiving social protection programs were identified by modeling the classification of households using the random forest technique, obtaining important variables using the permutation feature importance and Shapley additive explanations interpretation techniques, and analyzing the most important variables from the two interpretations methods. Handling the imbalance data on the response variables using SMOTE technique and evaluating the classification model obtained an AUC value of 0,718. The important variables were selected from the permutation feature importance and Shapley additive explanation methods based on a consistent ranking at the top. Shapley’s additive explanation was more consistent than permutation feature importance. Six important, namely capita expenditure, education of the head of household, age of head of household, source of drinking water, floor area, and the number of household members.