ANALYSIS OF JOB SATISFACTION OF ACADEMICIANS THROUGH THE USE OF ARTIFICIAL NEURAL NETWORKS

The quality of higher education depends on many criteria. One of them is the job satisfaction of the academicians who are working in the universities. The highly satisfied academicians are expected to have better performance in education. There are many different factors that may affect the job satisfaction of the academicians. In this study, we analyzed whether there is a relation between some of these factors and the job satisfaction of the academicians through the use of Back-propagation multilayer perceptron algorithm. The results have shown that the job satisfaction is highly related with the factors analyzed and can be estimated through the use of this model.