Penerapan Metode Structural Equation Modeling (Sem) dalam Menentukan Pengaruh Kepuasan, Kepercayaan dan Mutu terhadap Kesetiaan Pasien Rawat Jalan dalam Memanfaatkan Pelayanan Rumah Sakit di RSUD Dr. Pirngadi Medan Tahun 2012

Abstract

Implementation of Structural Equation Modeling (SEM) Method in Determining the Effects of Satisfaction, Trust, and Quality towards Out Patients' Loyalty Using Hospital Services at Dr.Pirngadi Local General Hospital Medan in 2012. SEM (Structural Equation Modeling) is a statistical technique that can analyze a relationship pattern between a latent construct and its indicators, another latent construct with the other latent constructs, and a direct incorrect measurement. SEM is a statistical techniques that can test a series of relationships simultaneously. In this research a series of simultaneous relationship - satisfaction, trust, quality, and patient's loyalty is conducted. Patients are the most important persons in the hospital, both as the consumers of the medical services and as the hospital products. The patient's loyalty is not formed in a short time, but it is based on the patient's own experience from the consistent and repeated uses of hospital. The purposes of this research are to analyze the effects of satisfaction, trust, and the quality of services towards the patients by using the SEM at Dr. Pirngadi Hospital Medan in 2012. The results of the research show that the variable of service quality influences the patient's satisfaction (p=0,001), quality influences the trust (p=0,001), quality influences the loyalty (p=0,032), the satisfaction influences the loyalty (p=0,014) and trust influences the loyalty (p=0,004). The data with Fit model based on Goodness-of Fit Index criteria result in the Chi-Square evaluation 190,011, the significant level 0,073 and the value of RMSEA (0,026), GFI (0,935), AGFI (0,899), CMIN/df (1,166), TLI (0,984), and CFI (0,989). There is an indirect effect of quality services on loyalty through the satisfaction and trust variables that they are both called interference variables