MULTIDIMENSIONAL POVERTY MODELING IN CENTRAL JAVA, DI YOGYAKARTA, AND EAST JAVA PROVINCES
Abstract
Indonesia has a National Medium-Term Development Plan (RPJMN) for 2020-2024 to reduce the poverty rate to 6 to 7 percent. However, the poverty rate has only declined by less than one percent in the past year, indicating the need for optimization to achieve the goal. Despite being located in Java, the center of development and economy in Indonesia, the poverty rate in Central Java, DI Yogyakarta, and East Java still exceeds the national average. This study used SUSENAS 2023 March KOR data to address this challenge and examine the multidimensional indicators affecting poverty. The Alkire-Foster method was used to obtain the Multidimensional Poverty Index (MPI) number, which was then analyzed using the Structural Equation Model (SEM) with the Asymptotically Distribution-free (AD-f) method approach. SEM is used to observe latent variables that cannot be measured and the relationship between variables that form a multidimensional poverty index. AD-f method approach is used to overcome data non-normality in SEM processing. The study revealed that the percentage of multidimensional poverty in the three provinces is higher than monetary poverty due to the household unit of analysis used. The standard of living dimension was the most deprived in most households, followed by the health dimension. To tackle this issue, the study recommends optimizing access to the Internet, assets, preschool participation, and nutrition.
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