Prediksi Luas Area Kebakaran Hutan Berdasarkan Data Meteorologi Dengan Menggunakan Pendekatan Multivariate Adaptive Regression Splines (Mars)

The purpose of this study is to develop a Non-parametric Path with the MARS (Multivariate Adaptive Regression Spline) approach which is applied to the behavior of paying credit compliance at Bank. prospective debtor by a Bank. The data used in this study is primary data using a research instrument in the form of a questionnaire. There are 7 variables, namely 5 exogenous variables in the form of 5C variables (Character (X1), Capacity (X2), Capital (X3), Collateral (X4), Condition of Economy (X5)), and two endogenous variables, namely Punctual Payment (Y1), Obedient Paying Behavior (Y2). Variable measurement technique is done by calculating the average score on the items. Sampling in this study used a purposive sampling technique with the criteria of respondents in the study were mortgage debtors (House Ownership Credit) at Bank X. Respondents obtained in this study were 100 respondents. The analysis used is nonparametric path with Multivariate Adaptive Regression Spline (MARS) approach. The result of this research is the estimation of nonparametric Path function using MARS approach on various interactions. The best estimate of the function of obedient behavior in paying credit is when it involves 4 variables, namely Character (X1), Capacity (X2), Conditions of economy (X5), and On time pay (Y1) with a value of generalized cross-validation The smallest (GCV) obtained is 0.2496. The originality of this research is the development of a nonparametric path with the MARS approach that is able to capture interactions between existing variables and is also able to handle the limitations of the truncated spline to determine the position and number of knot points used when involving many predictor variables. There has been no previous research that has examined the development of a nonparametric path with the MARS approach.

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Development of Nonparametric Path Model using Multivariate Adaptive Regression Spline (MARS) Method In Compliance Behavior of Paying Credit In Bank

Krisnawati

Fernandes

Solimun

2021

Wseas Transactions on Systems and Control

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Nonparametric Path Analysis on Consumer Satisfaction and Consumer Engagement in PT Pertamina

Fernandes

Solimun

Muflikhah

et al. 2022

Wseas Transactions on Mathematics

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The purpose of this research is to apply nonparametric path analysis on consumer satisfaction and consumer engagement of PT Pertamina. The results of the analysis are expected to be able to provide an estimate of the function in determining consumer satisfaction and consumer engagement of PT Pertamina. This study uses primary data involving five variables, namely Digitalization (X1), Consumer Needs (X2), Consumer Service (X3), Consumer Satisfaction (Y1), Consumer Engagement (Y3). Variable measurement technique is done by calculating the average score on the items. Sampling in this study used a purposive sampling technique with the respondent's criteria being company leaders. The result of this research is the estimation of nonparametric Path function using MARS approach on various interactions. The best estimate of the function of obedient behavior in paying credit is when it involves 3 variables, namely the digitization variable (X1), Consumer Needs (X2), Consumer Service (X3) with a value ofgeneralized cross-validation The smallest (GCV) obtained is 0.2833. The originality of this research is that the variables used are the results of DNA analysis (Discourse Network Analysis), where the analysis extracts information from cyberspace which is then formed as the main issue and becomes a variable. In addition, there is no previous research that examines nonparametric path analysis on PT Pertamina's consumer satisfaction and engagement.The purpose of this research is to apply nonparametric path analysis on consumer satisfaction and consumer engagement of PT Pertamina. The results of the analysis are expected to be able to provide an estimate of the function in determining consumer satisfaction and consumer engagement of PT Pertamina. This study uses primary data involving five variables, namely Digitalization (X1), Consumer Needs (X2), Consumer Service (X3), Consumer Satisfaction (Y1), Consumer Engagement (Y3). Variable measurement technique is done by calculating the average score on the items. Sampling in this study used a purposive sampling technique with the respondent's criteria being company leaders. The result of this research is the estimation of nonparametric Path function using MARS approach on various interactions. The best estimate of the function of obedient behavior in paying credit is when it involves 3 variables, namely the digitization variable (X1), Consumer Needs (X2), Consumer Service (X3) with a value ofgeneralized cross-validation The smallest (GCV) obtained is 0.2833. The originality of this research is that the variables used are the results of DNA analysis (Discourse Network Analysis), where the analysis extracts information from cyberspace which is then formed as the main issue and becomes a variable. In addition, there is no previous research that examines nonparametric path analysis on PT Pertamina's consumer satisfaction and engagement.

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Prediksi Luas Area Kebakaran Hutan Berdasarkan Data Meteorologi Dengan Menggunakan Pendekatan Multivariate Adaptive Regression Splines (Mars)

Cited by 2 publications

References 1 publication

Development of Nonparametric Path Model using Multivariate Adaptive Regression Spline (MARS) Method In Compliance Behavior of Paying Credit In Bank

Development of Nonparametric Path Model using Multivariate Adaptive Regression Spline (MARS) Method In Compliance Behavior of Paying Credit In Bank

Nonparametric Path Analysis on Consumer Satisfaction and Consumer Engagement in PT Pertamina

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