One of the spatial regression analysis used is the spatial durbin model (SDM). This model can be applied to obtain the relationship between X and Y variables and their spatial effects. This research was continued by testing the local spatial autocorrelation, namely the local indicator of spatial autocorrelation (LISA) which aims to provide information on the pattern of spatial relationships of each observation area in Bone Bolango regency. Stunting cases in Gorontalo province, especially in Bone Bolango regency, are in a status that needs to be addressed immediately due to the prevalence rate in Bone Bolango regency in 2019 above 20% based on the WHO standard. The results showed that the factors that significantly affected stunting in 2019 in Bone Bolango regency were exclusive breastfeeding, the  proper sanitation and poverty. Meanwhile, based on the spatial effect, the factors that significantly affected stunting in 2019 in Bone Bolango regency were the percentage of exclusive breastfeeding, the percentage of LBW, the number of children with CBI and poverty. Based on result from the LISA, the observation areas of stunting cases showed that the percentage of exclusive breastfeeding, the number of children with CBI and povertu had a spatial autocorrelation or forming a grouping on the distribution of the stunting cases, the number of children with IDL and poverty, there are sub-districts that have spatial autocorrelation.