SEMIVARIOGRAM MODEL ANALYSIS OF FOREST AND LAND FIRE DISTRIBUTION BASED ON CONFIDENCE LEVEL OF HOTSPOT IN KETAPANG REGENCY (WEST KALIMANTAN) - Ratna Gumilang, Ari
Forest and land fires are one of the common problems that occur in Indonesia. Forest and land fires have several negative impacts on the environtment, economy, and public health. Forest and land fires can be detected by hotspots. Hotspot is a point that has a relatively high temperature compared to the surrounding temperature. Confidence level is the level of confidence that hotspots in an area are actual occurences of forest and land fires in the field. West Kalimantan is one of the provinces that experiences forest fires every year, especially Ketapang Regency. Therefore, in this final project will discuss about the ditribution of forest and land fires based on confidence level of hotspots in Ketapang Regency. Confidence level of hotspots is included the spatial data because it is a random variable with location parameter. In this final project, we will determine a semivariogram anisotropy model that represents data. There are three theoretical semivariogram models used, there are exponential model, Gauss model, and spherical model. The data used in this final project is data on September 19, 2019 in Ketapang Regency. This hotspot data is divided into three regions based on the density between points in order to obtain a good model that represent the data. The model that represents the first, second, and third region is an exponential model. The unobserved point was estimated using the ordinary kriging method. The unobserved point obtained from the location of people’s oil palm plantation in Ketapang Regency. The estimation of the confidence level of the point ????0=(110.31176,?0.81304) which is in first region is 0.7567796, the point ????0=(110.198185,?1.982976) which is in second region is 0.8569518, and the point ????0=(110.93904,?2.69087) which is in third region is 0.8434843.