Analisis faktor-faktor sukses sistem e-payment

Jurnal Riset Sains Manajemen

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Title Analisis faktor-faktor sukses sistem e-payment
Analisis faktor-faktor sukses sistem e-payment
 
Creator Reza, Yuki
 
Description Purposes - At the end of the first decade of the 21st century, the term Fintech has expanded to include technological innovations in the financial sector, such as innovation in financial literacy, personal banking, commercial banking, investment and so on. In Indonesia, Fintech is the second most popular thing after e-commerce. This study aims to determine the factors that influence the use of Fintech in this case the use of E-payment.
Methods - In this study using primary data obtained by distributing questionnaires to employees of the Medan branch of PT. Wilmar Consultancy Services. The data is then analyzed using Factor Analysis to see how many factors are formed from 25 indicators which initially are groupings of five factors.
Findings - The results showed that there were 8 factors formed, namely the first factor Connectivity, the second factor Performance, the factors namely Efficiency, the fourth factor Promotion, the fifth factor of Service, the factor sixth Security, the seventh factor Advantage and finally the eighth factor Comfort. The access time (Waktu Akses) factor has the highest factor loading value which is equal to 0.870 which has the most influence among other factor indicators. And the item with the lowest value is a diversity (Keragaman) indicator that has a factor loading value of 0.552.
Keywords - Factor analysis, eigenvalues, principal component analysis (pca), rotation varimax, e-payment
Purposes - At the end of the first decade of the 21st century, the term Fintech has expanded to include technological innovations in the financial sector, such as innovation in financial literacy, personal banking, commercial banking, investment and so on. In Indonesia, Fintech is the second most popular thing after e-commerce. This study aims to determine the factors that influence the use of Fintech in this case the use of E-payment.
Methods - In this study using primary data obtained by distributing questionnaires to employees of the Medan branch of PT. Wilmar Consultancy Services. The data is then analyzed using Factor Analysis to see how many factors are formed from 25 indicators which initially are groupings of five factors.
Findings - The results showed that there were 8 factors formed, namely the first factor Connectivity, the second factor Performance, the factors namely Efficiency, the fourth factor Promotion, the fifth factor of Service, the factor sixth Security, the seventh factor Advantage and finally the eighth factor Comfort. The access time (Waktu Akses) factor has the highest factor loading value which is equal to 0.870 which has the most influence among other factor indicators. And the item with the lowest value is a diversity (Keragaman) indicator that has a factor loading value of 0.552.
Keywords - Factor analysis, eigenvalues, principal component analysis (pca), rotation varimax, e-payment
 
Publisher Lembaga Penelitian dan Penulisan Ilmiah AQLI
 
Date 2019-02-28
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
Peer-reviewed Article
 
Format application/pdf
 
Identifier http://ejurnal.id/index.php/jsm/article/view/234
 
Source Jurnal Riset Sains Manajemen; Vol 3 No 1 (2019): JRSM7; 31-48
Jurnal Riset Sains Manajemen; Vol 3 No 1 (2019): JRSM7; 31-48
2597-4726
 
Language ind
 
Relation http://ejurnal.id/index.php/jsm/article/view/234/106
 

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