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Determinants of the UMEGA model development in the use of the rental payment system
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Purpose: This research was conducted with the aim of analyzing the factors that influence the use of the rental payment system (SIMBAH-E) by adopting the UMEGA model as a technology acceptance model.
Methodology/approach: The data analysis method in this research used Structural Equation Modeling (SEM) with the Partial Least Square (PLS) approach. processed via the SmartPLS 4.0 application.
Findings: The results of this study show that there is a significant positive influence on the six independent latent variables on attitudes, there is one dependent variable that has a significant negative influence on attitudes, and one variable has no influence on attitudes and interest in use.
Practical implications: As well as latent variables of accounting information quality as a form of model development. The researcher used a questionnaire as a research measuring tool, and used a Likert scale in his assessment and used cluster random sampling in selecting respondents with a total of 100 respondents.
Originality/value: This research was conducted because the UMEGA model is the newest technology acceptance model so not many people have researched it, and this research contributes the latest thinking by adding a latent variable for the quality of accounting information as a development of the UMEGA model. Researchers used latent variables in the UMEGA model, namely performance expectations, effort expectations, social factors, risk of facilitating conditions, perceived risk, attitudes and interest in use.
Universitas Muhammadiyah Malang
Title: Determinants of the UMEGA model development in the use of the rental payment system
Description:
Purpose: This research was conducted with the aim of analyzing the factors that influence the use of the rental payment system (SIMBAH-E) by adopting the UMEGA model as a technology acceptance model.
Methodology/approach: The data analysis method in this research used Structural Equation Modeling (SEM) with the Partial Least Square (PLS) approach.
processed via the SmartPLS 4.
0 application.
Findings: The results of this study show that there is a significant positive influence on the six independent latent variables on attitudes, there is one dependent variable that has a significant negative influence on attitudes, and one variable has no influence on attitudes and interest in use.
Practical implications: As well as latent variables of accounting information quality as a form of model development.
The researcher used a questionnaire as a research measuring tool, and used a Likert scale in his assessment and used cluster random sampling in selecting respondents with a total of 100 respondents.
Originality/value: This research was conducted because the UMEGA model is the newest technology acceptance model so not many people have researched it, and this research contributes the latest thinking by adding a latent variable for the quality of accounting information as a development of the UMEGA model.
Researchers used latent variables in the UMEGA model, namely performance expectations, effort expectations, social factors, risk of facilitating conditions, perceived risk, attitudes and interest in use.
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