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GENERALIZED CONFIRMATORY FACTOR ANALYSIS FOR KNOWING IMPACT OF KNOWLEDGE, ATTITUDES, AND BEHAVIORAL FACTORS HIV/AIDS IN INDONESIA Rahmi, Nur Silviyah; Astutik, Suci; Astuti, Ani Budi; Muhammad, Alifiandi Rafi; Maisaroh, Ulfah; Handayani, Sri
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 2 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss2pp0695-0706

Abstract

The cumulative number of detected HIV/AIDS cases in the January – March 2021 period is 9,327, consisting of 7,650 HIV and 1,677 AIDS reported by 498 districts and cities from 514 districts and cities in Indonesia. Human Immunodeficiency Virus (HIV) is the virus that causes Acquired Immunodeficiency Syndrome (AIDS). Several factors that influence the spread of HIV/AIDS include knowledge, attitudes and behavior about HIV/AIDS. Someone who gains knowledge about HIV/AIDS will have high self-confidence and a positive outlook on life and be more optimistic in taking HIV/AIDS prevention actions. The main objective of this study is to determine the influence of external factors which include demographic, social and economic aspects, as well as internal factors which include knowledge, attitudes and behavior to the level of transmission of HIV/AIDS. By using the CFA approach, it can be seen which indicators have the greatest influence on the latent variables of knowledge, attitudes, and behavior or called loading factors. The data used is secondary data from a 5-year survey from the Central Statistics Agency, namely the 2017 Indonesian Demographic and Health Survey (IDHS) published at the end of 2018. The CFA results show that the P11 variable (about known infections) has the largest loading factor value, which is 0.613 in the variable. . hidden. knowledge. In the latent variable of attitude, the S1 variable (about identifying how the respondent knows someone is infected with HIV-AIDS) has the largest loading factor value of 0.514. While the behavioral latent variable, the variable R8 (whether men have been infected with sexually transmitted diseases (STI) with symptoms) has the largest loading factor value, which is 0.954.
STRUCTURAL EQUATION MODELING MULTIGROUP INDIRECT EFFECTS ON BANK MORTGAGE PAYMENT TIMELINESS Maisaroh, Ulfah; Fernandes, Adji Achmad Rinaldo; Iriany, Atiek
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 4 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss4pp2359-2366

Abstract

Structural Equation Modeling (SEM) is a multivariate statistical method that is used to thoroughly explain the relationship between latent variables simultaneously. Until now, SEM continues to grow in research. This research was conducted to examine the indirect effect on the timeliness of paying bank mortgages with a multi-group moderation approach. Analysis to identify factors that influence the timeliness of paying bank mortgages is an important step for banks before extending credit to prospective customers. The data used in this research is secondary data from research grants from National Competitive Basic Research. The data scale used is the Likert scale for exogenous, mediating endogenous, and pure endogenous variables. While the moderating variable uses a dummy variable. The results of the study show that the indirect effect of Capacity and Capital on Pay on Time for Bank Mortgage customers has a significant effect, both on non-current collectibility status and current collectibility status. This is evidenced by the Sobel test value greater than (1.96) on the indirect effect test, and the p-value of the Wald test is smaller than (0.05) on the moderation indirect effect test. Mediator variable is able to increase the effect of exogenous variables on endogenous variable Customers with current collectibility status have a stronger influence on timely payments than customers with non-current collectibility status.
Comparison of Mediation Effects on Interaction and Multigroup Approach in Structural Equation Modeling PLS in Case of Bank Mortgage Maisaroh, Ulfah; Fernandes, Adji Achmad Rinaldo; Iriany, Atiek; Ullah, Mohammad Ohid
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 8, No 1 (2024): January
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v8i1.19919

Abstract

“Structural Equation Modeling is one of multivariate statistical method that used to explain multiple relationships between latent variables simultaneously to test a mediation model to conduct a formal test on mediation effects. Application PLS-SEM for exploratory research and theory development are increasing. Under certain conditions, the effect of exogenous variables on endogenous variable is also strengthened or weakened by moderating variable. In SEM, there are two approaches in analyzing moderation variables, namely the interaction method and the multigroup method. This article aims to compare the mediation effect on interaction approaches and multigroup approaches in Structural Equation Modeling. The data used is the case of timeliness of Bank X mortgage payments. In this article, statistical methods are evaluated to compare indirect effect between groups and examine indirect effect on each group. It was concluded that Collectability Status moderates the indirect relationship between Capital and the Timeliness of Payment through Willingness to Pay. Debtors with current collectability status more strongly effect the Timeliness of Payment than debtors with incurrect collectability status. Theresults of testing indirect effects on moderation with interaction and multigroup approaches are not much different. In the multigroup approach, the bootstrap interval bias is smaller than the bootstrap interval bias in the interaction approach. The Q-square Predictive Relevance value in both methods is quite high, indicating that the model is good. On the Current Collectibility Status group Q^2 is 89.3%, in the incurrect Collectibility Status Q^2 is 84.2%. While in the interaction approach, Q^2 is 70.4%. Researcher recommend a multigroup approach to data that has categorical moderation variables because differences between groups can be directly observed without adding interaction variables in the model.”