Abstract:
Spatial autocorrelation is an analytical method for measuring the similarity between attributes in a space. The occurrence of spatial randomness indicates the presence of spatial patterns such as clustered, scattered or random. One of the method of measure spatial autocorrelation is Moran's I method or Moran's Index. Moran's Index is commonly used to see events such as forest fire disasters. The forest fires that occurred in Kalimantan Tengah had a very damaging impact. Apart from destroying the environment, forest fires also causing health problems and affecting the community's economy, especially for those who depend on forest products. The purpose of this study is to visualize and determine the shape of the distribution of cases of forest and land fires in Kalimantan Tengah Province using Moran's I statistical measurements. The data and methods used are maps and data on the area of ??forest and land fires in regency/manicipality in Kalimantan Tengah Province in 2018-2022 obtained from the Ministry of Environment and Forestry of the Republic of Indonesia. The results of this study shows that the distribution of forest fires from 2018 to 2022 are known to have no significant changes, while between regions tend to have similarities with their neighbors. And it is concluded that forest and land fires occur randomly or not in groups and there is no spatial autocorrelation.
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