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Farisiyah Fitriani
Departemen Statistika, Fakultas Sains dan Matematika, Universitas Diponegoro

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PENERAPAN METODE GENERALIZED STRUCTURED COMPONENT ANALYSIS PADA KEPUASAN KONSUMEN (Studi Kasus: Pasien Klinik Q) Farisiyah Fitriani; Agus Rusgiyono; Tatik Widiharih
Jurnal Gaussian Vol 9, No 4 (2020): Jurnal Gaussian
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/j.gauss.v9i4.29416

Abstract

Customer satisfaction is used by a company to evaluate products or services whether it is sufficient with customer’s expectations. Satisfaction is influenced by factors that cannot be measured directly are called latent variables and can be measured through indicators used to measure satisfaction with Structural Equation Modeling (SEM). Generalized Structured Component Analysis (GSCA) method is part of a SEM based on a variant that does not require the assumption of a multivariate normal distribution and has a measure overall goodness of fit. The parameters used are factor loading, coefficients parameter, and weight of indicators and estimated with alternating least square. The type of data used primary data from the results of the questionnaire with stratified proportional random sampling and number of samples 286. This research using indicators as measurable variables as many 32 indicators and 8 latent variable. Considering to the evaluation of the structural model, it is found there are 5 variables that influence satisfaction, they are prices, quality yield, cleanliness, doctor's services, and employee services with a large influence of 77.18% and the impact of satisfaction on loyalty is 48.63 %. For the overall goodness of fit measure, it is known that the FIT value is 63.75% and the adjusted FIT (AFIT) value is 63.47%. The goodness of fit (GFI) produced the value in the amount of 96.43%, indicating that the general model has the good level of compatibility.Keywords: Generalized Structured Component Analysis, Structural Equation Modeling, Overall goodness of fit, Alternating Least Square, Stratified Proportional Random Sampling