The community capacity building program in reducing disaster risk aims to realize the Bandung Rejo village as a disaster resilient village. Efforts made to achieve community capacity building include: (1) institutional aspects through the establishment of Disaster Risk Management forums (DRR) and Community Disaster Preparedness Teams (CDPT), (2) aspects of capacity building through dissemination and training in the preparation of disaster management plans and contingency plans , (3) aspects of the implementation of disaster management through a program to create a threat map and create disaster warning signs. The establishment of DRR and CDPT forums has a strategic role in minimizing disaster risk. The results achieved from the socialization and training were the availability of Bandung Rejo village disaster risk analysis document. The document can be a reference in making development policies in the village. Based on the results of the analysis conducted by the forum that Bandung Rejo village had a flood hazard level in the medium category. The results of identification and analysis obtained two flood-prone points that were able to reach agricultural land and facilities and infrastructure facilities. The implementation of community capacity building programs in Bandung Rejo village can provide stimulus to local governments and the public about the importance of disaster anticipation.

Information on household poverty level in Wonosari Sub-district area is still very difficult to access by all parties. Therefore, this study aims to analyze poverty level and map of the spatial distribution of webGIS-based poor households in the site area. In determining the number of samples, descriptive statistical analysis techniques focused on assessing and describing the poverty level of each household. GIS analysis used GIS Application 2.18 to map the spatial distribution of poor households and regional poverty levels. GIS Application has been equipped with 2 web tools that are able to display webGIS-based maps. The results shows that the poverty level of households is in the poor category with a percentage of 72% of households, 14% of households are in the extremely poor category and 14% are in the fairly poor category. and 1 village is in a fairly poor category. This is a village that was built with a view that can be accessed by various PCs, laptops and android media so that the maps information from an analysis of household poverty levels and the spatial distribution of poor households can be accessed on the webGIS that has been built.