REDESIGNING CONSOLIDATED DATA FOR HANDLING EXTREME POVERTY IN RURAL AREAS BASED ON SDGS DESA

Abstract

Responses to extreme poverty include ensuring the authenticity of related data. Therefore, studies of data consolidation on handling extreme poverty in rural areas are important. The integration of poverty studies into social science and development fields is crucial for advancing knowledge in these disciplines. This study aims to describe data inequality and collection accuracy in Indonesia. It used a data consolidation approach based on SDGs Desa to explore the disparity in central and regional poverty data collection, which impacts the loss of access to basic rights. Furthermore, this study relied on survey data from 100 villages in 4 of the 5 regencies piloting the projects to tackle extreme poverty in East Java, Indonesia. The results showed that the accuracy of the data influenced the poor categorization, social assistance distribution, and the seriousness of the state in alleviating extreme poverty. Therefore, it becomes the basis for further study in unravelling the dynamics in the design of data collection in rural areas.