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All Journal Media Statistika CAUCHY: Jurnal Matematika Murni dan Aplikasi BAREKENG: Jurnal Ilmu Matematika dan Terapan
Amanda, Devi Veda
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Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Energy Engineering Mathematics Mechanical Engineering Physics Transportation

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EXPLORE THE DETERMINANTS OF CUSTOMERS TIME TO PAY HOUSE OWNERSHIP LOAN ON DATA WITH HIGH MULTICOLLINEARITY WITH PCA-COX REGRESSION Ramadhan, Rangga; Fimba, Adfi Bio; Fernandes, Adji Achmad Rinaldo; Solimun, Solimun; Junianto, Fachira Haneinanda; Amanda, Devi Veda; Sumara, Rauzan
MEDIA STATISTIKA Vol 17, No 2 (2024): Media Statistika
Publisher : Department of Statistics, Faculty of Science and Mathematics, Universitas Diponegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14710/medstat.17.2.117-127

Abstract

One of the models in survival analysis is the Cox proportional hazards model. This method ignores assumptions regarding the distribution of survival times studied. If there are indications of multicollinearity in data handling, one way that can be done is to use PCA (Principal Component Analysis). PCA-Cox regression is a combination of survival analysis and PCA which can be an alternative in analyzing multicollinearity survival data. The large number of cases of bad credit means that customers must be careful in providing credit to prospective customers. Character, capacity, capital and collateral variables are thought to influence the length of time customers pay house ownership loans at the bank. The data used is secondary data (n=100) regarding the assessment of character variables, capacity, capital and collateral, credit collectibility, and time to pay customer house ownership loans at the bank. The results of the analysis using PCA-Cox regression show that the variables character, capacity, capital and collateral have a significant effect on the length of house ownership loan payment time for Bank X customers. The originality of this research is the use of the PCA-Cox regression integration model in bank credit risk analysis.
ANALYSIS OF PATH NONPARAMETRIC TRUNCATED SPLINE MAXIMUM CUBIC ORDER IN BANKING CREDIT OF RISK BEHAVIOR MODEL Amanda, Devi Veda; Iriany, Atiek; Fernandes, Adji Achmad Rinaldo; Solimun, Solimun
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 4 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss4pp2639-2652

Abstract

Path analysis tests the relationship between variables through cause and effect. The assumption of linearity must be met before conducting further tests on path analysis. If the shape of the relationship is nonlinear and the shape of the curve is unknown, a nonparametric approach is used, one of which is a truncated spline. The purpose of this study is to estimate the function and obtain the best model on the nonparametric truncated spline path of linear, quadratic, and cubic orders with 1 and 2-knot points and determine the significance of the best function estimator in banking credit of risk behavior model through the jackknife resampling method. This study uses secondary data through questionnaires to KPR debtor consumers, as many as 100 respondents. Based on the results of the analysis, it is known that the best-truncated spline nonparametric path model is the quadratic order of 2 knots with a coefficient of determination of 85.50%; the significance of the best-truncated spline nonparametric path estimator shows that all exogenous variables have a significant effect on endogenous variables.
Structural Equation Modeling Semiparametric Truncated Spline in Banking Credit Risk Behavior Models Amanda, Devi Veda; Iriany, Atiek; Fernandes, Adji Achmad Rinaldo; Solimun, Solimun
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 10, No 1 (2025): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v10i1.29769

Abstract

Housing is one of the primary needs for every individual. Along with the increasing population growth in Indonesia, the need for housing has also experienced a significant surge. This study aims to analyze the effect of customer attitudes on compliance behavior, fear of paying late, and timeliness of payment on Home Ownership Credit (KPR) customers at X Bank. Using a semiparametric Structural Equation Modeling (SEM) approach, this study examines the relationship between these variables to provide a deeper understanding of the factors that influence customer payment behavior. The data used in this study are primary data obtained through questionnaires distributed to 100 Bank X mortgage customers. The results of the analysis show that there is a significant influence between customer attitudes (X1) on obedient payment behavior (Y1) and fear of paying late (Y2), as well as timeliness of payment (Y3). The estimated coefficients obtained show a positive relationship between compliance behavior and timeliness of payment, and a negative relationship between fear of paying late and timeliness of payment, with a p-value 0.001 indicating statistical significance. This finding indicates that good customer attitudes can improve payment timeliness, while poor attitudes can lead to fear of paying late, which in turn can affect payment timeliness.
Co-Authors Atiek Iriany Fernandes, Adji Achmad Rinaldo Fimba, Adfi Bio Junianto, Fachira Haneinanda Ramadhan, Rangga Solimun, Solimun Sumara, Rauzan