ANALISIS VARIABEL INDEKS PEMBANGUNAN MANUSIA MENGGUNAKAN ANALISIS REGRESI LINIER BERGANDA DI PROVINSI JAWA TIMUR - MUNAWAROH, SARIFUL; GANDHIADI, G.K.; NILAKUSMAWATI, DESAK PUTU EKA (E-Jurnal Matematika, 2023)
According to the Central Statistics Agency, HDI is formed by three basic dimensions, namely life expectancy, knowledge, decent living standards. So researchers are interested in analyzing the influence of these 3 basic dimensions on HDI using multiple linear regression analysis. By determining the independent variables and dependent variables, human development index data in East Java in 2021. Then determining the estimated value of the multiple regression model. Next, carry out testing, starting with a simultaneous test. After that, a partial test (t test) was carried out. Then the classical assumption test is carried out, which is a statistical requirement that must be met in multiple linear regression analysis. In multiple regression analysis, classic assumption tests are carried out, including the normality test, multicollinearity test and heteroscedasticity test. Then look at the coefficient of determination value to find out how far the model is able to explain variations in the dependent variable. The final step in this research is to interpret the model with multiple linear regression, namely to see and explain the results of the best model analysis and find out the independent variable that has the most significant influence on the dependent variable. Research data analysis was carried out using SPSS software. The multiple linear regression model formed in the analysis of the human development index in East Java obtained a contribution value from the independent variable and the dependent variable of 99.7%.