Regresi Multivariabel Bayes Pada Kasus Konversi Lahan Pertanian - Hastuti, Yuli (Innovative: Journal Of Social Science Research, 2022)
Multivariable regression analysis with Bayes estimation taking into account the real nature of the data and sample data information from previous observations. This method is a nonparametric method that tolerates classical regression assumptions. The focus of the research is to find out the factors that influence land conversion in the Regency/City of South Sulawesi. The study compared the results of the classical regression model with the Bayesian multivariable regression model in the land conversion case. Estimation of parameters using the Bayesian approach using cojugates before normal distribution. Based on the sensitivity of the parameter estimation results and the RMSE value, it means that the multivariable Bayesian regression is better than the classical regression model. The rate of population growth, the percentage of population density, the percentage of the total population, and the gini ratio has a significant positive effect on the proportion of villages that cause the conversion of agricultural land to non-agricultural land at a 95% increase in confidence.