DEVELOPMENT OF CLUSTER INTEGRATION WITH VARIAN BASED STRUCTURAL EQUATION MODELING TO MANAGE HETEROGENEOUS DATA
In the application of SEM to multivariate data, the individuals collected not only come from the same population but also from several groups (clusters). This data is heterogeneous. When SEM is applied to heterogeneous data, there will be a risk of bias in estimating equations in the measurement and...
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Universitas Pattimura
2025-04-01
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| Series: | Barekeng |
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| Online Access: | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/15464 |
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| author | Hanifa Sepriadi Atiek Iriany Solimun Solimun Adji Achmad Rinaldo Fernandes |
| author_facet | Hanifa Sepriadi Atiek Iriany Solimun Solimun Adji Achmad Rinaldo Fernandes |
| author_sort | Hanifa Sepriadi |
| collection | DOAJ |
| description | In the application of SEM to multivariate data, the individuals collected not only come from the same population but also from several groups (clusters). This data is heterogeneous. When SEM is applied to heterogeneous data, there will be a risk of bias in estimating equations in the measurement and structural models because there are differences between groups in the data. The purpose of this study is to overcome heterogeneous data in modeling cashless behavior with cluster using a dummy approach. This study used primary data from a survey in Bekasi City using a questionnaire with 100 respondents. Based on the study's results, it is known that using clustering in SEM can overcome heterogeneous data, which is indicated by the high coefficient of determination of 96.12%. Banks can use the results of this study to design products and services that are more in line with customer needs and preferences while encouraging financial inclusion in the digital era. |
| format | Article |
| id | doaj-art-d531076e90194822b1f1e9657f5fbb39 |
| institution | Kabale University |
| issn | 1978-7227 2615-3017 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Universitas Pattimura |
| record_format | Article |
| series | Barekeng |
| spelling | doaj-art-d531076e90194822b1f1e9657f5fbb392025-08-20T03:41:56ZengUniversitas PattimuraBarekeng1978-72272615-30172025-04-011921193120210.30598/barekengvol19iss2pp1193-120215464DEVELOPMENT OF CLUSTER INTEGRATION WITH VARIAN BASED STRUCTURAL EQUATION MODELING TO MANAGE HETEROGENEOUS DATAHanifa Sepriadi0Atiek Iriany1Solimun Solimun2Adji Achmad Rinaldo Fernandes3Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Brawijaya, IndonesiaDepartment of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Brawijaya, IndonesiaDepartment of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Brawijaya, IndonesiaDepartment of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Brawijaya, IndonesiaIn the application of SEM to multivariate data, the individuals collected not only come from the same population but also from several groups (clusters). This data is heterogeneous. When SEM is applied to heterogeneous data, there will be a risk of bias in estimating equations in the measurement and structural models because there are differences between groups in the data. The purpose of this study is to overcome heterogeneous data in modeling cashless behavior with cluster using a dummy approach. This study used primary data from a survey in Bekasi City using a questionnaire with 100 respondents. Based on the study's results, it is known that using clustering in SEM can overcome heterogeneous data, which is indicated by the high coefficient of determination of 96.12%. Banks can use the results of this study to design products and services that are more in line with customer needs and preferences while encouraging financial inclusion in the digital era.https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/15464cashless societyclusterheterogeneousstructural equation modeling |
| spellingShingle | Hanifa Sepriadi Atiek Iriany Solimun Solimun Adji Achmad Rinaldo Fernandes DEVELOPMENT OF CLUSTER INTEGRATION WITH VARIAN BASED STRUCTURAL EQUATION MODELING TO MANAGE HETEROGENEOUS DATA Barekeng cashless society cluster heterogeneous structural equation modeling |
| title | DEVELOPMENT OF CLUSTER INTEGRATION WITH VARIAN BASED STRUCTURAL EQUATION MODELING TO MANAGE HETEROGENEOUS DATA |
| title_full | DEVELOPMENT OF CLUSTER INTEGRATION WITH VARIAN BASED STRUCTURAL EQUATION MODELING TO MANAGE HETEROGENEOUS DATA |
| title_fullStr | DEVELOPMENT OF CLUSTER INTEGRATION WITH VARIAN BASED STRUCTURAL EQUATION MODELING TO MANAGE HETEROGENEOUS DATA |
| title_full_unstemmed | DEVELOPMENT OF CLUSTER INTEGRATION WITH VARIAN BASED STRUCTURAL EQUATION MODELING TO MANAGE HETEROGENEOUS DATA |
| title_short | DEVELOPMENT OF CLUSTER INTEGRATION WITH VARIAN BASED STRUCTURAL EQUATION MODELING TO MANAGE HETEROGENEOUS DATA |
| title_sort | development of cluster integration with varian based structural equation modeling to manage heterogeneous data |
| topic | cashless society cluster heterogeneous structural equation modeling |
| url | https://ojs3.unpatti.ac.id/index.php/barekeng/article/view/15464 |
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