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Robust PCA Using MCD and MM Estimators in MARS A Simulation Study Uswatun Hasanah; Solimun Solimun; Atiek Iriany
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 11, No 2 (2026): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v11i2.41547

Abstract

Multivariate Adaptive Regression Splines (MARS) models nonlinear relationships through adaptive basis functions but remain sensitive to outliers in the predictor variables. Existing robust extensions of MARS primarily address response outliers, while the few studies integrating Robust Principal Component Analysis (RPCA) with MARS use RPCA only for dimension reduction without comparing robust estimators. This study evaluates RPCA as a robust predictor transformation and systematically compares two robust covariance estimatorsthe Minimum Covariance Determinant (MCD) and the MM-estimatorwithin the RPCA-MARS framework. A full factorial simulation with 100 replications per condition covered 45 conditions: five sample sizes (n = 50, 100, 200, 500, 1000), three outlier proportions (5%, 10%, 25%), and three MARS interaction levels (1, 2, 3) with eight predictor variables. Outliers were extreme values in a specified proportion of predictor observations. Performance was measured by Root Mean Square Error (RMSE). For analysis, the 45 conditions were collapsed into 15 scenarios by selecting the interaction level with the minimum RMSE for each sample size and outlier proportion. The MM estimator outperformed the MCD estimator in 8 of 15 scenarios, achieving lower RMSE under moderate-to-high outlier contamination (10%25%) with moderate sample sizes (n = 100500). MCD performed better in the remaining 7 scenarios: under low contamination (5%) at n 200 and n 1000, and across all contamination levels at n = 1000. MCD showed higher variability at small samples with moderate-to-high contamination, while MM produced tighter confidence intervals and lower standard deviations. Within the RPCA-MARS framework, MM is recommended for moderately sized, highly contaminated data, while MCD is preferable under low contamination or in large-scale settings.
Nonparametric Path Modeling with Double Resampling for Waste Economic Value Utilization: Simulation-Based Performance Comparison Kamelia Hidayat; Adji Achmad Rinaldo Fernandes; Atiek Iriany; Solimun Solimun; Moh. Zhafran Hidayatulloh; Fachira Haneinanda Junianto
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 10, No 2 (2025): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v10i2.37218

Abstract

Waste generation exceeding landfill capacity highlights the urgency of realizing its economic value. This study analyzes the effect of Quality of Facilities and Infrastructure (X1) and Use of Waste Banks (X2) on Waste Management-Based 3R (Y1) and Waste Economic Value Utilization (Y2) using a truncated spline nonparametric path model. This study evaluates the performance of a nonparametric path analysis model based on truncated spline combined with a double resampling. Data were collected using a Likert scale questionnaire on community perceptions of waste’s economic benefits in Batu City. Simulation results show that the Jackknife-Bootstrap method achieves the lowest average bias (0.058), outperforming single resampling approaches such as Single-Bootstrap (0.178) and Single-Jackknife (0.176). Empirical findings indicate that improvements in the Quality of Facilities and Infrastructure  (X1) and Waste Bank Use (X2) significantly enhance Waste Management Based 3R (Y1) and Utilization of Waste Economic Value (Y2). The truncated spline model reveals a saturation effect, where the marginal benefits of X1 and X2 decrease beyond a threshold. Furthermore, Y1 positively affects Y2, emphasizing the importance of efficient waste management in enhancing economic value. The results support policies promoting balanced infrastructure development, community empowerment, and institutional innovation for sustainable circular economy implementation.
Sensitivity of Bayesian Truncated Spline Regression to Prior and Knot Configuration in Stunting Models Septi Nafisa Ulluya Zahra; Adji Ahmad Rinaldo Fernandes; Achmad Efendi; Solimun Solimun; Alfiyah Hanun Nasywa; Fachira Haneinanda Junianto
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 10, No 2 (2025): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v10i2.37381

Abstract

This study develops a Bayesian bi-response regression model using a truncated spline approach to examine nonlinear effects of economic, dietary, and environmental factors on nutritional and physical stunting. Sensitivity analysis was conducted to evaluate the influence of prior types and knot numbers on model performance using Deviance Information Criterion (DIC), Root Mean Square Error (RMSE), and bias. Results show that the informative Normal–Gamma prior combination yields the best performance, with the lowest DIC, smallest RMSE, and minimal bias. Models with three knots provide higher predictive accuracy, while noninformative Uniform priors cause instability and overfitting. Overall, the findings indicate that prior specification has a stronger effect on model robustness than the number of knots, emphasizing the importance of informative priors in Bayesian spline modeling for understanding complex, nonlinear determinants of child stunting.
THE PERCEPTION OF INDIVIDUAL AND ORGANIZATIONAL CAREERS IN INCREASING THE ORGANIZATIONAL COMMITMENT Rahmi Widyanti; Armanu Thoyib; Margono Setiawan; Solimun Solimun
Journal of Economics, Business, and Accountancy Ventura Vol. 15 No. 2 (2012): August 2012
Publisher : Universitas Hayam Wuruk Perbanas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14414/jebav.v15i2.77

Abstract

Organization commitment is very important for individuals working in any organization.Therefore, considering individuals and the perception toward the careers is really important.This study determines the direction of influence of basic individual careers and career developmentprograms on job satisfaction and organizational commitment. This research conducteda survey on Private Higher Education teaching staff of Kopertis (private higher educationcoordinator) Borneo in Banjarmasin. The data from 60 respondents were analyzedusing the Partial Least Square (PLS) to examine the relationship among variables basic individualcareers and career development programs that have a significant and positive impacton job satisfaction and organizational commitment. The results showed that the basic individualcareers and career development programs affect organizational commitment and jobsatisfaction. In addition, it is also proved that job satisfaction mediate the increasing organizationalcommitment.
Integration of DBSCAN Cluster Analysis with Multigroup Moderation Path Analysis Hafizh Syihabuddin Al Jauhar; Solimun Solimun; Rahma Fitriani
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 10, No 1 (2025): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v10i1.29847

Abstract

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.
Modified Ramsey RESET in Combined Truncated Spline–Fourier Nonparametric Path Analysis on Waste Management Behavior Moh Zhafran Hidayatulloh; Solimun Solimun; Adji Achmad Rinaldo Fernandes; Anggun Fadhila Rizqia; Fachira Haneinanda Junianto
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 10, No 2 (2025): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v10i2.37239

Abstract

Nonparametric path analysis is a statistical approach that does not require the functional form of relationships between variables to be known a priori. Classical path analysis assumes linearity, which can be tested using the Ramsey Regression Specification Error Test (RESET). If the linearity test indicates that the relationships between variables are nonlinear, a nonparametric model can be applied. The purpose of this study is to develop a modified Ramsey RESET to identify nonparametric relationships modeled using truncated spline and Fourier series. The modified Ramsey RESET algorithm was successfully implemented to detect the optimal functional form of the nonparametric truncated spline and Fourier series and was subsequently applied to behavioral data on waste management practices. Furthermore, this study proposes an estimator for a hybrid nonparametric path model combining truncated spline and Fourier series approaches. The analysis results reveal that the best model integrates truncated spline with one and two knot points and a Fourier series with one oscillation. The model achieved an adjusted coefficient of determination of 0.956, indicating that it explains 95.6% of the variation in the Behavior of Transforming Waste into Economic Value, while the remaining 4.4% is explained by other unobserved factors outside the model.
Integrating Path Analysis and Kendall’s Tau-based Principal Component Analysis to Identify Determinants of Child Health Viky Iqbal Azizul Alim; Atiek Iriany; Adji Achmad Rinaldo Fernandes; Solimun Solimun; Candra Rezzining Wulat Sariro Weni Utomo
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 10, No 2 (2025): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v10i2.31156

Abstract

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.
Spearman Rank Correlation PCA for Mixed Scale Indicator in Structural Equation Modeling Lisa Asaliontin; Eni Sumarminingsih; Solimun Solimun; Mohammad Ohid Ullah
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 10, No 1 (2025): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v10i1.29976

Abstract

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).
A Combined Truncated Spline and Kernel Semiparametric Path Model Development Usriatur Rohma; Adji Achmad Rinaldo Fernandes; Suci Astutik; Solimun Solimun
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 10, No 1 (2025): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v10i1.29849

Abstract

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.
Structural Equation Modeling Semiparametric Truncated Spline in Banking Credit Risk Behavior Models Devi Veda Amanda; Atiek Iriany; Adji Achmad Rinaldo Fernandes; Solimun Solimun
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 10, No 1 (2025): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Maulana Malik Ibrahim State Islamic University of 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 Achmad Efendi Adji Achmad Rinaldo Fernandes Adji Ahmad Rinaldo Fernandes Agus Fachrur Rozy Agustina, Evi Lusi Al Jauhar, Hafizh Syihabuddin Alfiyah Hanun Nasywa Ali Djamhuri Amanda, Devi Veda Angga Dwi Mulyanto Anggun Fadhila Rizqia Arief Rachmansyah Aries Budianto Arini, Luthfia Hanun Yuli Armanu Thoyib Armanu Thoyib Asaliontin, Lisa Atiek Iriany Azizah, Amelia Nur Azizah, Maulida Balqis, Nabila Azarin Bambang Semedi Bonifasia Elita Bharanti Budiyanto Budiyanto Candra Dewi Candra Rezzining Wulat Sariro Weni Utomo Devi Veda Amanda Dewi Yanti Liliana Dirman, Eris Nur Djumahir .. Djumilah Hadiwidjojo Djumilah Zain Endang Arisoesilaningsih Endang Setyawati Eni Sumarminingsih Eni Sumarminingsih Evellin Dewi Lusiana, Evellin Dewi Fachira Haneinanda Junianto Fachira Haneinanda Junianto Fernandes, Adji Achmad Rinaldo Fimba, Adfi Bio Firman Iswahyudi Mustopo Gultom, Fandi Rezian Pratama Hafizh Syihabuddin Al Jauhar Halim .. Hamdan, Rosita Hamdan, Rosita Binti Handoyo, Samingun Hardianti, Rindu Hidayat, Kamelia Ida Nur Hidayati Istiqomah, Nur Junainto, Fachira Haneinanda Junianto, Fachira Haneinanda Kamelia Hidayat Kurniasari, Lia Lisa Asaliontin Loekito Adi Soehono Loekito, Loekito Luthfatul Amaliana, Luthfatul M. Agung Wibowo, M. M.S Idrus Made Subudi Margono S. Margono Setiawan Meilina Retno Hapsari Meirina, Risk Mintarti Rahayu Mitakda, Maria Bernadetha Moh Zhafran Hidayatulloh Moh. Zhafran Hidayatulloh Mohammad Ohid Ullah Mudjiono Mudjiono, Mudjiono Muh. Arif Rahman Muh. Arif Rahman Musran Munizu Ni Wayan Surya Wardhani Ni Wayan Surya Wardhani Nuddin Harahab Nurjannah Nurjannah Nurjannah Padma Devia, Y. Papalia, M. Fikar Permatasari, Kiky Ariesta Pramaningrum, Dea Saraswati Pratama, Yossy Maynaldi Pusaka, Semerdanta Qomariyatus Sholihah Rahma Fitriani Rahma Fitriani Rahmanda, Lalu Ramzy Rahmi Widyanti Ramadhan, Rangga Ramifidiosa, Lucius Rejeki, Sasi Wilujeng Sri Rinaldo Fernandes, Adji Achmad Rohma, Usriatur Rohman, Muhammad Zainur Saputra, Yoyok Yuni Sepriadi, Hanifa Septi Nafisa Ulluya Zahra Sianipar, Celia Suci Astutik Sumara, Rauzan Sumarminingsih, Eni Surachman .. Theresia Mitakda, Maria Bernadetha ubud sallim Ullah, Mohammad Ohid Usriatur Rohma Uswatun Hasanah Utama, Risha Ardasari Viky Iqbal Azizul Alim Wayan Firdaus Mahmudy Wayan Sri Kristinayanti Yulianto, Shalsa Amalia Yulvi Zaika Zahra, Septi Nafisa Ulluya Zaki Yamani Zamelina, Armando Jacquis Federal