(untitled) (Jurnal Teknodik, 2018)
Factor analysis is a test of construct validity. The test is taken by testing so much items or variables and extracting to be lesser and simpler factors. The extraction is carried by unifying some items or variables having significant common variance as they measure the same dimension. In its application, factor analysis can be exploratory or confirmatory. Exploratory factor analysis is used to understand some factors explaining a variabel that analysis does not work under a hyphotesis. On the other hand, confirmatory factor analysis hyphotezise some factors from some items or variables to guide its work. The analysis runs some steps : testing of analysis property, serving correlation matrix, doing extraction, making rotation, and labeling factors. The results of testing are interpreted in some ways. Data can be analyzed if assumptions are approved. Index of Kaiser Meyer Olkin must be over 0,80. Data must also be normal in Bartlet’s test of sphericity. Items or variables make the same dimension or factor if they have intercolinnearity over 0,20. A factor can be developed if it has eigenvalues more than 1,00. An item support a factor if it has factor loadings more than 0,30. Then, the developed factors are labelled or named according to the characteristic of supporting items.