Confirmatory factor analysis: model testing of financial ratios with decision support systems approach

Abstract

The decision support systems approach can be developed into both computer-based and quantitative analysis tools. This research uses a model test with a confirmatory factor analysis (CFA) technique on matrix covariance against structural equation modelling (SEM) methods to measure financial ratios. Decision support system (DSS) analysis uses numerical calculations aided by mathematical models through six phases. The first three phases of a structured approach to building multivariate models and the next three phases, namely estimation, interpretation, and validation, are developing from data input that has been selected using LISREL version 8.72. The financial ratio’s testing model with a CFA approach derived into a mathematical (quantitative) model can explain the complexity of the relationship between the goodness-of-fit models (GOF) with a different approach from prior research. The goodness-of-fit test results in this study produced scores on each of the financial ratio measurement models at an accuracy level of CR of 78.49, TATO of 1.26, DER of 41.41, ROA of minus 0.033, and PBV of 540.92. This means that PBV has the highest standardized loading factors to determine the measurement of financial ratios. The CFA measurement based on SEM can be used to make appropriate decisions and combine a model comparison and redevelopment of the CFA technique and model testing with other software such as SPSS, PLS, AMOS, and others.