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All Journal Media Statistika CAUCHY: Jurnal Matematika Murni dan Aplikasi BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) Ecces: Economics, Social, and Development Studies JSMARTech : Journal of Smart Bioprospecting and Technology Jurnal Teknik Informatika (JUTIF) MATHunesa: Jurnal Ilmiah Matematika SEMINAR NASIONAL PENELITIAN DAN PENGABDIAN KEPADA MASYARAKAT Journal of Statistics and Data Science
Fernandes, Adji Achmad Rinaldo
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Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Energy Engineering Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Nursing Physics Social Sciences Transportation Other

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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.”
PERFORMANCE OF NEURAL NETWORK IN PREDICTING MENTAL HEALTH STATUS OF PATIENTS WITH PULMONARY TUBERCULOSIS: A LONGITUDINAL STUDY Rahmanda, Lalu Ramzy; Fernandes, Adji Achmad Rinaldo; Solimun, Solimun; Ramifidiosa, Lucius; Zamelina, Armando Jacquis Federal
MEDIA STATISTIKA Vol 16, No 2 (2023): 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.16.2.124-135

Abstract

Comorbidity between pulmonary tuberculosis and mental health status requires effective psychiatric treatment. This study aims to predict anxiety and depression levels in patients with pulmonary tuberculosis and consider future mental health treatment for patients. A sample of 60 pulmonary tuberculosis patients in Malang were involved and evaluated longitudinally every two weeks over 13 periods. In this study, we use the Generalized Neural Network Mixed Model (GNMM) to obtain better results in predicting anxiety and depression levels in patients with pulmonary tuberculosis and compare the results with the Generalized Linear Mixed Model (GLMM). The flexibility of GLMM in modeling longitudinal data, and the power of neural network in performing a prediction makes GNMM a powerful tool for predicting longitudinal data. The result shows that neural network's prediction performance is better than the classical GLMM with a smaller MSPE and fairly accurate prediction. The MSPEs of the three compared models: 1-Layer GNMM, 2-Layer, and GLMM, respectively are 0.0067, 0.0075, 0.0321 for the anxiety levels, and 0.0071, 0.0002, and 0.0775 for the depression levels. Furthermore, future research needs to investigate the data with a larger sample size or high dimensional data with large network architectures to prove the robustness of GNMM.
PENAMBAHAN METODE NEURAL NETWORK DALAM PEMODELAN GSTAR-SUR UNTUK MENGATASI KASUS NON LINIER PADA PERAMALAN DATA CURAH HUJAN Iriany, Atiek; Fernandes, Adji Achmad Rinaldo; Efendi, Achmad; Putri, Henida Ratna Ayu; Ariyanto, Danang; Ngabu, Wigbertus
MATHunesa: Jurnal Ilmiah Matematika Vol. 12 No. 1 (2024)
Publisher : Universitas Negeri Surabaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26740/mathunesa.v12n1.p226-236

Abstract

Salah satu model peramalan yang dapat yang menggabungkan unsur spasial (spatial) dan temporal (time) adalah Generalized Space Time Autoregressive (GSTAR). Pendugaan parameter yang digunakan adalah Seemingly Unrelated Regression (SUR). Peramalan iklim pada tanaman hortikultura pada masa kini sulit untuk diprediksi karena memiliki pola dan karakteristik yang sulit diidentifikasi dan dapat disebut aktivitas non linier. Unsur non linier ini dapat ditangkap oleh metode neural network. Penelitian ini ingin mengetahui hasil peramalan curah hujan pada 6 wilayah di Tengger menggunakan model GSTAR dengan pendugaan parameter menggunakan metode SUR dan digabungkan dengan neural network agar hasil peramalan yang lebih akurat. Data yang digunakan dalam penelitian ini adalah data curah hujan enam lokasi di wilayah Tengger, yakni Ngadirejo, Puspo, Wonokitri, Argosari, Ngadas, dan Wonokerto. Model yang tepat dalam melakukan peramalan pada data curah hujan pada 6 lokasi Tengger adalah model GSTAR (1,2,3,4,5,6,7,36(1)) Backpropagation Neural Network (96-120-6).
Modelling Geographically Weighted Truncated Spline Regression Using Maximum Likelihood Estimation for Human Development Disparities Saris, Laode Muhammad; Pramoedyo, Henny; Fernandes, Adji Achmad Rinaldo
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.v10i1.31381

Abstract

A development of nonparametric truncated spline regression, Geographically Weighted Regression Spline Truncated (GWSTR) incorporates spatial effects in the modelling of nonlinear relationships between the response and predictor variables. This research utilizes the Maximum Likelihood Estimation (MLE) technique to estimate the parameters of the model. The first-order truncated spline with a single knot yielded a minimal Generalized cross-validation (GCV) value of 1. 729781, suggesting a high level of accuracy in the model.  Four weighting functions were evaluated: Gaussian Kernel, Exponential Kernel, Bi-Square Kernel, and Tri-Cube Kernel. Among these, the Bi-Square weighting function performed the best, achieving a coefficient of determination of 99.999%, demonstrating the model’s capability to explain nearly all data variability effectively. GWSTR proves to be a robust method for capturing complex nonlinear relationships while accounting for spatial variations, making it a valuable tool for spatial data analysis across various disciplines.
Simulation Study and Development of Semiparametric Multiresponse Multigroup Truncated Spline Regression for Rice Pest Control Azizah, Laila Nur; Fernandes, Adji Achmad Rinaldo; Wardhani, Ni Wayan Surya
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.v10i1.29773

Abstract

Rice pest control is a critical challenge in the agricultural sector that requires a deep understanding of rice pest management. Regression analysis is a statistical method capable of describing and predicting cause-and-effect relationships between individuals. In real-life applications, not all relationships exhibit a known curve pattern, and non-identifiable curve forms are often observed. Additionally, a single cause may affect more than one outcome, and the outcomes themselves can have interrelationships. Such relationships can be approached through a multi-response semiparametric regression using a truncated spline multi-group model. This study aims to develop a multi-response semiparametric multi-group regression model using the truncated spline approach to understand the variables influencing rice pest control under light and dark conditions. This model is applied to secondary and simulated data with various scenarios to determine the best model. The study results indicate that the optimal model for secondary data is a semiparametric regression model with a linear order and a single knot point, achieving a determination coefficient of 89.17%. Simulation results show that the scenario 1 model (linear with a single knot point) produces a high determination coefficient. This multi-response regression model proves more optimal when error variance and multicollinearity levels are kept low to moderate.
Development of Semiparametric Smoothing Spline Path Analysis on Cashless Society Nurdin, Muhammad Rafi Hasan; Ullah, Muhammad Ohid; Fernandes, Adji Achmad Rinaldo; Sumarminingsih, Eni; 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.v10i1.29846

Abstract

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
A Combined Truncated Spline and Kernel Semiparametric Path Model Development Rohma, Usriatur; Fernandes, Adji Achmad Rinaldo; Astutik, Suci; 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.v10i1.29849

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 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.
Educational Workshop Berbasis HOTS: Upaya Meningkatkan Kualitas Guru SMP dan SMA pada Olimpiade Guru Nasional Fernandes, Adji Achmad Rinaldo; Lusia, Dwi Ayu; Nisa, Hilwin; Hidayatulloh, Moh Zhafran; Rizqia, Anggun Fadhila; Nasywa, Alfiyah Hanun; Putri, Nazwa Anindya; Amirullah, Khoirul Insan
Seminar Nasional Penelitian dan Pengabdian Kepada Masyarakat 2025 Prosiding Seminar Nasional Penelitian dan Pengabdian Kepada Masyarakat (SNPPKM 2025)
Publisher : Universitas Harapan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35960/snppkm.v4i1.1411

Abstract

The National Teacher Olympiad (OGN) is a prestigious event that aims to improve teacher competence, especially in the field of mathematics, through mastery of pedagogy, learning innovation, and the application of Higher Order Thinking Skills (HOTS). However, junior and senior high school teachers in Malang Regency still face obstacles in the form of limited access to training, lack of professional community, and low literacy in learning technology. This service program was carried out at PP & SMA Sumber Putih, Malang Regency, with the aim of strengthening teacher competence through strategies to strengthen positive mindsets, increase motivation, and interactive training based on Higher Order Thinking Skills. The implementation method includes educational workshops, motivational sessions, group discussions, preparation of learning modules, and reflection to measure the effectiveness of the program. The results of the activity showed an increase in teachers' mental readiness in facing the National Teachers' Olympiad, strengthening the understanding of Higher Order Thinking Skills in mathematics learning, and improving technological skills in the learning process. In addition, training modules are arranged as outputs that can be used continuously. This program contributes to improving the professionalism of teachers, encouraging participation in OGN, and building an innovative and competitive education ecosystem in Malang Regency.
Modified Ramsey RESET in Combined Truncated Spline–Fourier Nonparametric Path Analysis on Waste Management Behavior Hidayatulloh, Moh Zhafran; Solimun, Solimun; Fernandes, Adji Achmad Rinaldo; Rizqia, Anggun Fadhila; Junianto, Fachira Haneinanda
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 10, No 2 (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.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.
Co-Authors Achmad Efendi Al Jauhar, Hafizh Syihabuddin Alim, Viky Iqbal Azizul Amanda, Devi Veda Amirullah, Khoirul Insan Arini, Luthfia Hanun Yuli Atiek Iriany Azizah, Laila Nur Bakar, Normizan bin Danang Ariyanto Eni Sumarminingsih Fimba, Adfi Bio Hamdan, Rosita Hamdan, Rosita Binti Henny Pramoedyo Hidayat, Kamelia Hidayatulloh, Moh Zhafran Hidayatulloh, Moh. Zhafran Junainto, Fachira Haneinanda Junianto, Fachira Haneinanda Khairani, Aldianur Khairina, Nadia Lusia, Dwi Ayu Maisaroh, Ulfah Marchamah, Mamlu’atul Nasywa, Alfiyah Hanun Ni Wayan Surya Wardhani Nisa, Hilwin Nurdin, Muhammad Rafi Hasan Nurjannah Nurjannah Nurjannah Pramaningrum, Dea Saraswati Pratama, Yossy Maynaldi Putri, Henida Ratna Ayu Putri, Nazwa Anindya Rahma Fitriani Rahman R, Abd Rahmanda, Lalu Ramzy Ramadhan, Rangga Ramifidiosa, Lucius Ramifidisoa, Lucius Rejeki, Sasi Wilujeng Sri Rizqia, Anggun Fadhila Rohma, Usriatur Sabir Sabir Saris, Laode Muhammad Solimun Solimun, Solimun Suci Astutik Sumara, Rauzan Ullah, Mohammad Ohid Ullah, Muhammad Ohid Utomo, Candra Rezzining Wulat Sariro Weni Wigbertus Ngabu Yulianto, Shalsa Amalia Zamelina, Armando Jacquis Federal Zuhdi, Muhammad Rizal