| dc.description.abstract | Structural Equation Modeling (SEM) is a class of multivariate techniques that
combine aspects of factor analysis and regression, enabling the researcher to
simultaneously examine relationships among measured variables and latent
variables as well as between latent variables. Meanwhile, partial least square is
soft modeling approach to SEM without any assumptions about data distribution
and minimal number of observation that often called as PLS SEM. Data that used
in this research are the province’s data in Indonesia that has 34 provinces. The
number of observation that equals to 34 observations is too small and could not
fulfill the maximum likelihood estimation of SEM. In this research, the estimation
method used was PLS, so the analysis called PLS SEM. This research used the
PLS SEM to identify the factors that influence the human development index
based on the province’s data in Indonesia. Human Development Index consists of
three dimensions, which are Economy, Education, and Health that used as latent
variables that influence the human development index direct and indirectly. The
result of this research show that Economy and Health influence the Human
Development Index directly significant. Education influences Human
Development Index indirectly with partial mediation that mediated by Economy.
The model in this research is evaluated by Q2 value that equals to 67% so the
model obtained from this research was good enough In explaining the variance of
Human Development Index. | id |
