Panel spatial regression is a regression used to model panel data that contains spatial effects. In spatial data, the use of classical regression cannot be used. It will result in inaccurate conclusions because in spatial data it is often found the influence of a location with other locations that are close to each other. The purpose of this study is to find the form of a panel spatial regression model on the human development index data and identify the factors that influence the human development index in districts/cities in Central Java Province. This study focuses on modeling the human development index in districts / cities in Central Java Province using the Spatial Autoregressive (SAR) model and the Spatial Error Model (SEM). As the result, the best model is the Spatial Autoregressive Fixed Effect Model. Significant variables are the number of health workers, the school participation rate for ages 16-18 years old, the number of poor people, and the district/city minimum wage.