Analisis Autokorelasi Spasialtitik Panas Di Kalimantan Timur Menggunakan Indeks Moran dan Local Indicator Of Spatial Autocorrelation (LISA) - Nurmalia Purwita Yuriantari; Memi Nor Hayati; Sri Wahyuningsih (Program Studi Statistika FMIPA Universitas Mulawarman, 2017)
In the last few decades has developed statistical methods relating to spatial science, is the spatial statistics. Spatial Statistics aims to analyze spatial data. The case studies in this study was the amount of hotspots in East Kalimantan by Regency/City in years 2014-2016. This study aimed to analyze the existence of spatial autocorrelation in the data the amount of hotspots as well as determine the level of vulnerability to potential areas of forest and land fires in East Kalimantan by Regency/City in 2014-2016. The method used to analyze the global spatial autocorrelation is the Moran Index method and Local Indicators of Spatial Autocorrelation (LISA) for analyze spatialautocorrelation locally. The results of the analysis of global spatial autocorrelation using the Moran index with α = 20% showed there spatial autocorrelation amount of hotspots in East Kalimantan in 2014, 2015, and 2016. Meanwhile, the analysis results locally using LISA showed that there spatial autocorrelation in several Regency/City in East Kalimantan in 2014, 2015 and 2016. The analysis results Regency/City that belong to the vulnerable category of forest and land fires is Bontang City, Kutai Barat Regency, Kutai Kartanegara Regency, Mahakam Ulu Regency, dan Penajam Paser Utara Regency and Samarinda City.