ANALISIS MODEL EMPIRIK DALAM MELANJUTKAN STUDI DI PERGURUAN TINGGI DI BIDANG ASURANSI
Abstract
Empirical analysis is an analysis obtained from data that has been observed by a researcher conducted through an experiment or making data on its own. One empirical analysis used is the Structural Equation Model (SEM). SEM is based on causality, where changes in one variable will change the other variables. One form of relationship patterns can be described through path analysis obtained using the SPSS application. Before the data is analyzed, test the reliability of the data with Cronbach’s Alpha. The experimental data used in this study were the analysis of the factors that cause students to continue their studies in university (economic factors, parental education and family environment) and analysis of the factors that cause students to choose to continue their studies in insurance (welfare factors after graduation and interest). On the data of continuing studies in university, the Cronbach's Alpha score is 0.804 and on the data of continuing study interest is 0.862. Both data are greater than 0.6 so it can be said that both data are reliabel. The data of continuing studies in university, which have the highest level of effect on continuing studies to tertiary education is parental education. In the interest analysis data which has a higher effect to measure interest in continuing studies in the insurance field is the level of economic welfare.
References
Andrews, J.D dan Moss, T.R. (2002). Reliability and Risk Assessment. The American Society of Mechanical Engineers, New York.
Bollen, K.A dan Pearl, J. (2013). Eight Myth about Causality and Structural Equation Models, Handbook of causal analysis for social research. Springer, New York.
Ghozali, I. (2013). Aplikasi Analisis Multivariate dengan Program IBM SPSS 21 Update PLS Regresi Edisi VII. Badan Penerbit Universitas Diponegoro, Semarang.
Lakshmi,S dan Mohideen, M.A. (2013). Issues in Reliability and Validity of Research. International Journal of Management Research and Review. 3(4) 2752-2758.
McCue, C. (2006). Data Mining and Predictive Analysis Intelligence Gathering and Crime Analysis. Jordan Hill: Elsevier.
Pemerintah RI. (2017). Statistik Perasuransian Insurance Statistics 2017 [internet]. https://www.ojk.go.id/id/kanal/iknb/data-dan-statistik/asuransi/Documents/Pages/Statistik-Perasuransian-Indonesia---2017/Buku%20Statistik%20Perasuransian%202017.pdf. (diakses tanggal 16 April 2019).
Rai, B.K. dan Singh, N. (2009). Reliability Analysis and Prediction with Warranty Data Issues, Strategies and Methods. CRC Press, London.
Schumacker, RE dan Lomax, RG. (2004). A Beginner’s Guide to Structural Equation Modeling Ed. 2nd. Lawrence Erlbaum Associates, Inc., London.
Wolberg, J. (2010). Designing Quantitative Experiments Prediction Analysis. Springer, New York.