Special model of susceptible district of dengue fever in Ngemplak Subdistrict, Boyolali

Abstract

As an effort of prevention of Dengue Fever Occurence, it must be applied an information system which is able to give fast, exact, complete, and easy understood information. Because of that, it needs to be developed a Geographical Information System {Sistem Informasi Geografis (SIG)} in society health service, that is related to the distribution and risking factors of Dengue Fever Occurence. The Geographical Information System model can show the description of spacial distribution of Dengue Fever cases in a district, the tendency of illness spreading, and whether there is clustering of the illness or not, so it can identify unsafe/susceptible level in a district to Dengue Fever Occurrence. The design of this research is observational analytic with Cross Sectional approach, using Geographical Information System in spacial analysis. The samples of the research are all dengue fever victims recorded at public health centre in Ngemplak Subdistrict, Boyolali Regency from 2016 to 2017, which are 93 respondents. The data analysis is done by univariate, bivariate with Contingency Coefficient test and spacial analysis in Geographical Information System approach. The result of the recearch shows risking factors that is proved significantly related to dengue fever occurence. Those are population density percentage (p=0.003) and the number of free mosquito larva percentage (p=0.001). Spacialy, districts in Ngemplak Subdistrict, Boyolali, that have highest susceptible level to dengue fever are Sindon and Gagak Sipat village.