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<![CDATA[Power Of Test Path Analysis and Partial Least Square Analysis ]]>
<![CDATA[Kurniawan, Arif]]>;
<![CDATA[Loekito, Loekito]]>;
<![CDATA[Solimun, Solimun]]>
<![CDATA[ CAUCHY Vol 4, No 3 (2016): CAUCHY ]]>
Publisher : <![CDATA[Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang ]]>
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DOI: 10.18860/ca.v4i3.3593
<![CDATA[Path analysis Analysis and Partial Least Square (PLS) was used to analyze many variables. Both methods use the least squares method (OLS) that can be compared between the two to determine the best method in a study to get an assessment of the behavior of civil servants in the Government of Kediri. The purpose of this study is: comparing path analysis Analysis with Partial Least Square (PLS) on the power of the test and the valueR2.Path method is able to provide the value of R2 higher than Analysis of Partial Least Square (PLS) but the value of the test power analysisi path is smaller than using Analysis of Partial Least Square (PLS). Usage analysis methods Path Analysis and Partial Least Square (PLS) produces behavioral assessment of civil servants in the government of Kediri is nearly equal results and discussion. Based on the analysis to prove that the behavior of civil servants in the Government of Kediri not meet eligibility based on the grade levels and echelons of the civil service]]>
<![CDATA[Multigroup Moderation Test in Generalized Structured Component Analysis ]]>
<![CDATA[Mulyanto, Angga Dwi]]>;
<![CDATA[Solimun, Solimun]]>;
<![CDATA[Wardhani, Ni Wayan Surya]]>;
<![CDATA[Suharno, Suharno]]>
<![CDATA[ CAUCHY Vol 4, No 2 (2016): CAUCHY ]]>
Publisher : <![CDATA[Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang ]]>
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DOI: 10.18860/ca.v4i2.3491
<![CDATA[Generalized Structured Component Analysis (GSCA) is an alternative method in structural modeling using alternating least squares. GSCA can be used for the complex analysis including multigroup. GSCA can be run with a free software called GeSCA, but in GeSCA there is no multigroup moderation test to compare the effect between groups. In this research we propose to use the T test in PLS for testing moderation Multigroup on GSCA. T test only requires sample size, estimate path coefficient, and standard error of each group that are already available on the output of GeSCA and the formula is simple so the user does not need a long time for analysis.]]>
<![CDATA[Integrating Path Analysis and Kendall’s Tau-based Principal Component Analysis to Identify Determinants of Child Health ]]>
<![CDATA[Alim, Viky Iqbal Azizul]]>;
<![CDATA[Iriany, Atiek]]>;
<![CDATA[Fernandes, Adji Achmad Rinaldo]]>;
<![CDATA[Solimun, Solimun]]>;
<![CDATA[Utomo, Candra Rezzining Wulat Sariro Weni]]>
<![CDATA[ CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 10, No 2 (2025): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI ]]>
Publisher : <![CDATA[Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang ]]>
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DOI: 10.18860/cauchy.v10i2.31156
<![CDATA[This study develops a latent variable path analysis model using a Mixed-Scale Principal Component Analysis (PCA) approach based on Kendall’s Tau correlation to identify key determinants of child health in Batu City, Indonesia. Primary data were collected from 100 mothers with children under five years old through questionnaires. The variables examined include Family Demographics, Nutritional Consumption, and Child Health Condition, each measured using mixed-scale indicators (ordinal and numerical). Kendall’s Tau-based PCA was applied to reduce data dimensionality and construct latent variables, which were then integrated into a path analysis model. The results show that maternal age is the most dominant indicator in shaping the Family Demographics construct, while balanced nutritional food is the strongest indicator forming the Nutritional Consumption construct. Path analysis further reveals that Family Demographics significantly affect Child Health Condition both directly and indirectly through Nutritional Consumption, with a coefficient of determination of 77.62\%. These findings underscore the critical role of demographic and nutritional factors in determining child health outcomes and highlight the methodological advantage of Kendall’s Tau-based mixed-scale PCA for analyzing heterogeneous indicator data within a structural path framework.]]>
<![CDATA[Development of Semiparametric Smoothing Spline Path Analysis on Cashless Society ]]>
<![CDATA[Nurdin, Muhammad Rafi Hasan]]>;
<![CDATA[Ullah, Muhammad Ohid]]>;
<![CDATA[Fernandes, Adji Achmad Rinaldo]]>;
<![CDATA[Sumarminingsih, Eni]]>;
<![CDATA[Solimun, Solimun]]>
<![CDATA[ CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 10, No 1 (2025): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI ]]>
Publisher : <![CDATA[Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang ]]>
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DOI: 10.18860/cauchy.v10i1.29846
<![CDATA[Path analysis requires assumptions to be met, particularly the linearity assumption, which can be tested using the Ramsey Regression Specification Error Test (RESET). Parametric path analysis is appropriate when all variable relationships are linear. For entirely non-linear relationships, a nonparametric model can be used, while a semiparametric model applies if there is a mix of linear and non-linear relationships. One nonparametric method is spline smoothing, which requires determining the spline polynomial order in estimating the nonparametric path function. Determining the spline polynomial order is challenging because there is no standard test for it. This study thus develops a modified Ramsey RESET to identify the optimal spline smoothing order. The development involves modifying the second regression equation with a nonparametric spline smoothing regression of orders 2 to 5. The modified Ramsey RESET algorithm is applied to cashless data, and the results are used to estimate a multi-group semiparametric smoothing spline function with a dummy variable approach. This estimation yields a goodness of fit of 94.14%, indicating that Product Quality and the Moderating Effect of Cashless Usage Frequency can explain Cashless User Satisfaction and Cashless User Loyalty by 94.14%, with the remaining 5.86% explained by variables outside the research model]]>
<![CDATA[Development of Semiparametric Truncated Spline Logistic Path Analysis ]]>
<![CDATA[Rejeki, Sasi Wilujeng Sri]]>;
<![CDATA[Solimun, Solimun]]>;
<![CDATA[Nurjannah, Nurjannah]]>;
<![CDATA[Yulianto, Shalsa Amalia]]>;
<![CDATA[Ullah, Muhammad Ohid]]>
<![CDATA[ CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 10, No 1 (2025): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI ]]>
Publisher : <![CDATA[Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang ]]>
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DOI: 10.18860/cauchy.v10i1.29979
<![CDATA[Logistic path analysis extends logistic regression by incorporating intervening variables, addressing the limitations of linearity assumptions through nonparametric models like spline regression. However, this study develops a semiparametric truncated spline logistic path analysis to accommodate linear and nonlinear relationships, considering direct and indirect effects of intervening variables. The model is applied to analyze the impact of price volatility and human resource quality on farmer welfare, with farmer productivity as an intervening variable. It assumes a nonlinear relationship between price volatility and productivity/welfare, while other relationships are linear. This development was applied to secondary data collected through questionnaires from farmer group members in Bali Province, which were analyzed using a semiparametric truncated spline logistic path model. Optimal knots were determined using the lowest GCV value. The results show that the model effectively captures changes in data patterns, providing robust parameter estimates. Hypothesis testing highlights significant differences in the effectiveness of linear and nonlinear relationships. The use of truncated splines offers critical insights into variable interactions and enhances model reliability, making it a valuable tool for analyzing complex agricultural systems and informing policies to improve farmer welfare and productivity.]]>
<![CDATA[Integration of DBSCAN Cluster Analysis with Multigroup Moderation Path Analysis ]]>
<![CDATA[Al Jauhar, Hafizh Syihabuddin]]>;
<![CDATA[Solimun, Solimun]]>;
<![CDATA[Fitriani, Rahma]]>
<![CDATA[ CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 10, No 1 (2025): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI ]]>
Publisher : <![CDATA[Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang ]]>
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DOI: 10.18860/cauchy.v10i1.29847
<![CDATA[This study examines the application of integration between DBSCAN cluster analysis and multigroup moderation path analysis to analyse patterns of waste management behaviour in Batu City. DBSCAN was used to cluster the data based on density, resulting in two main clusters as well as some noise data. The first cluster consisted of 189 respondents, while the second cluster included 196 respondents, with the remaining 10 data identified as noise. The DBSCAN clustering results showed a silhouette index of 0.664, indicating good clustering quality in terms of compactness and separation between clusters. After the data was clustered, each cluster was analysed using multigroup moderation path analysis to assess the relationship between environmental quality, understanding of 3R-based waste management, and economic usefulness of waste with facilities and infrastructure variables as moderators. The results showed that clusters with good quality facilities had a stronger understanding of 3R-based waste management and its economic usefulness. This finding underscores the importance of facilities and infrastructure in influencing community waste management behaviour patterns.]]>
<![CDATA[Spearman Rank Correlation PCA for Mixed Scale Indicator in Structural Equation Modeling ]]>
<![CDATA[Asaliontin, Lisa]]>;
<![CDATA[Sumarminingsih, Eni]]>;
<![CDATA[Solimun, Solimun]]>;
<![CDATA[Ullah, Mohammad Ohid]]>
<![CDATA[ CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 10, No 1 (2025): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI ]]>
Publisher : <![CDATA[Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang ]]>
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DOI: 10.18860/cauchy.v10i1.29976
<![CDATA[Structural Equation Modeling (SEM) is a statistical modeling technique that integrates measurement models and structural models simultaneously. In the SEM measurement model, not all latent variables are metric, they can be mixed scales, namely metric and non-metric which have not been widely studied. This study aims to apply the Spearman Rank Correlation Principal Component Analysis (PCA) to handle mixed-scale indicator data in a mixed measurement model (formative and reflective). This method is evaluated on a case study of fertilizer repurchase decisions, resulting in a total determination coefficient of 80%. This shows the flexibility of SEM in handling the complexity of mixed-scale data without sacrificing estimation accuracy. The results showed that the Spearman Rank Correlation PCA was able to store 78.62% of the diversity of data from mixed-scale indicator variables, namely Farmer Demographics (X2). In addition, the results showed that Customer Satisfaction (X1) significantly influenced Repurchase Decisions (Y2) but did not directly affect Customer Engagement (Y1). Farmer Demographics (X2) significantly influences Customer Engagement (Y1) and Repurchase Decisions (Y2), and Customer Engagement has a significant effect on Repurchase Decisions (Y2).]]>
<![CDATA[A Combined Truncated Spline and Kernel Semiparametric Path Model Development ]]>
<![CDATA[Rohma, Usriatur]]>;
<![CDATA[Fernandes, Adji Achmad Rinaldo]]>;
<![CDATA[Astutik, Suci]]>;
<![CDATA[Solimun, Solimun]]>
<![CDATA[ CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 10, No 1 (2025): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI ]]>
Publisher : <![CDATA[Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang ]]>
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DOI: 10.18860/cauchy.v10i1.29849
<![CDATA[Semiparametric path analysis is a combination of parametric and nonparametric path analysis performed when the linearity assumption in some relationships is not met. In this study, the development of semiparametric path function estimation was carried out by combining two truncated spline and kernel approaches. In addition, the purpose of this study is to determine the significance of function estimation using t-test statistics at the jackknife resampling stage. This research was conducted in 135 Junrejo sub-districts of Batu district. The results showed that the development of a combined semiparametric path function estimation of truncated spline and kernel with weighted least square allows a more flexible and accurate estimation in modeling waste management behavior patterns. 2. The significance of the best truncated spline nonparametric path estimation in the model of the effect of Environmental Quality and the Use of Waste Banks on the Economic Benefits of Waste through the Use of the 3R Principles using t test statistics at the jackknife resampling stage shows that all exogenous variables have a significant effect on endogenous variables.]]>
<![CDATA[Structural Equation Modeling Semiparametric Truncated Spline in Banking Credit Risk Behavior Models ]]>
<![CDATA[Amanda, Devi Veda]]>;
<![CDATA[Iriany, Atiek]]>;
<![CDATA[Fernandes, Adji Achmad Rinaldo]]>;
<![CDATA[Solimun, Solimun]]>
<![CDATA[ CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 10, No 1 (2025): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI ]]>
Publisher : <![CDATA[Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang ]]>
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DOI: 10.18860/cauchy.v10i1.29769
<![CDATA[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.]]>
