Clustering and visualization of community complaints and proposals using text mining and geographic information system

Urban planners have been striving to enhance citizens' participation in urban planning processes. In Indonesia, the Government of Jakarta developed an e-participation tool called e-Musrenbang to directly involve public in submitting complaints and proposals. However, there was no systematic method used by the Government to analyze and map a lot of complaints and proposals data. The big number of complaints and proposals requires data mining approach to automating the process of extracting knowledge from the data set. This study aimed to perform text clustering to obtain the specific topics of community reports and to visualize the intensity of each topic in the urban area. This study is a subsequent stage of research, after urban problem classification. The results of text clustering showed that majority of public complaints and proposals are associated with drainage and roadwork. This research showed the spread of public reports intensity in the urban area by visualizing the text clustering results using Geographic Information System.