Spatial Autocorrelation Analysis of Tuberculosis Cases (2016-2018) In Kebumen
Tuberculosis (TB) is one of the tenth highest causes of death in Indonesia and even worldwide. Tuberculosis is an infectious disease caused by an infection of Mycobacterium tuberculosis bacterium. Kebumen is one of the districts with high tuberculosis cases and tends to increase every year. Based on the high case number, it is necessary to start research that examines patterns of spread. Spatial analysis is a very useful tool to evaluate the spreading pattern of the tuberculosis disease according to its geographical location. The study aimed to spatially analyze tuberculosis spread pattern from 2016 to 2018 using the spatial autocorrelation method through Moran Index and Local Indicator of Spatial Association (LISA). The study showed that the spatial autocorrelation in the spreading patterns of tuberculosis occurred in Kebumen and had a clustered pattern because of Moran Index is positive. The results of the LISA analysis in the High-High quadrant showed that the high tuberculosis cases correlated with areas that also had high tuberculosis cases. Sixteen villages were included in the High-High quadrant.
 Glaziou, P., Sismanidis, C., Zignol, M. & Floyd, K. (2017). Methods used by WHO to estimate the global burden of TB disease. World Health Organization.
 Umi, R., Raja, K., Radzi, M., et al. (2011). Review of Mycobacterium Tuberculosis Detection. Control Syst. Grad. Res. Colloq. pp. 189–192.
 World Health Organization (WHO). (2018). Global Tuberculosis 2018 Report.
 Kebumen, D. K. Profil Kesehatan Kebumen 2017. (2017). Available at: https://kesehatan.kebumenkab. go.id/ (Accessed: 23rd October 2017).
 Kebumen, D. K. Profil Kesehatan Kebumen 2016. (2016). Available at: https://kesehatan.kebumenkab. go.id/ (Accessed: 23rd October 2017).
 Flynn, J. L. and Chan, J. (2001). IMMUNOLOGY OF TUBERCULOSIS. Annu Rev Immunol, vol. 19, pp. 93–129.
 Lee, J. & Wong, D. W. Statistical Analysis With Arcview GIS. ( John Willey & Sons. Inc, 2001).
 Chou, Y. (1995). Spatial Pattern and Spatial Autocorrelation. in Spatial Information Theory A Theoretical Basis for GIS, vol. 988, pp. 365–376.
 Fu, W. J., Jiang, P. K., Zhou, G. M. et al. (2014). Using Moran’s I and GIS to study the spatial pattern of forest litter carbon density in a subtropical region of southeastern China. Biogeosciences, vol. 2, pp. 2401–2409.
 Chen, Y. (2013). New Approaches for Calculating Moran ’ s Index of Spatial Autocorrelation. PLoS One, vol. 8.
 Pfeiffer, D. U., Robinson, T. P., Stevenson, M., (2008). (Techniques). Spatial Analysis in Epidemiology United Kingdom. vol. 19, pp. 148–149.
 Yang, Z., Lu, S. & Jin, X. (2011). Tourism Spatial Association Analysis Based on GIS Technology for the Cities in Anhui of China. Int. Conf. Geoinformatics, pp. 0–4.
 Prasannakumar, V., Vijith, H., Charutha, R. et al. (2011). Spatio-Temporal Clustering of Road Accidents: GIS Based Analysis and Assessment. Procedia – Soc. Behav. Sci. vol. 21, pp. 317–325.