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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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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.
Comparison of Nonparametric Path Analysis and Biresponse Regression using Truncated Spline Approach Azizah, Laila Nur; Rohma, Usriatur; Fernandes, Adji Achmad Rinaldo; Wardhani, Ni Wayan Surya; Astutik, Suci
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 9, No 1 (2025): January
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v9i1.26739

Abstract

Nonparametric path analysis and biresponse nonparametric regression are two flexible statistical approaches to analyze the relationship between variables without assuming a certain form of relationship. This study compares the performance of the two methods with the truncated spline approach, which has the advantage of determining the shape of the regression curve through optimal selection of knot points. This study aims to evaluate the best model based on linear and quadratic polynomial degree with 1, 2, and 3 knot points. The model is applied to data with 100 samples and simulated data of various sample levels. The results show that the best model in nonparametric path analysis is a quadratic model with three knots, while the best model in biresponse nonparametric regression is a quadratic model with two knots. Biresponse nonparametric regression has a coefficient of determination of 88.8% which is higher than the nonparametric path analysis of 70.9%. The best biresponse nonparametric regression model is the model with quadratic order and two knots.
Development of Ramsey RESET to Identify the Polynomials Order of Smoothing Spline with Simulation Study Nurdin, Muhammad Rafi Hasan; Fernandes, Adji Achmad Rinaldo; Sumarminingsih, Eni; Ullah, Muhammad Ohid
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 9, No 1 (2025): January
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v9i1.26785

Abstract

Path  analysis is used to determine the effect of exogenous variables on endogenous variables. One of the assumptions in path analysis is the linearity assumption. The linearity assumption can be tested using Ramsey RESET. If the Ramsey RESET results show that all variables are non-linear then one of the alternative models that can be used is nonparametric smoothing spline. The smoothing spline method requires a smoothing spline polynomial order in estimating the nonparametric path analysis function. This polynomial order results in the smoothing spline method having good flexibility in data adjustment. The selection of the smoothing spline polynomial order becomes an obstacle because there is no test to determine the best order. Therefore, the purpose of this study is to find out how the value of V for order 3 and 4, develop Ramsey RESET to identify the best spline polynomial order, and evaluate the Ramsey RESET algorithm through simulation studies on various errors. The results of V values of order 3 and 4 can be obtained through the integral process and it is found that the higher the order, the value of V has a higher rank. Ramsey RESET development is done by modifying the second regression using nonparametric regression functions of order 2, 3, and 4. The simulation study results show that the classical Ramsey RESET can be used to detect linear shapes well because it is not affected by the value of the error variance. However, the classical Ramsey RESET has limitations in detecting non-linear forms other than quadratic and cubic forms so that other forms such as smoothing spline are needed. In testing non-linear models, the lowest p value is obtained in the form that matches the actual conditions, this can be interpreted that the modified Ramsey RESET can detect non-linear forms with spline polynomial orders well. The contribution of this research is to provide a test to identify the best smoothing spline polynomial order using Ramsey RESET modification
COMPARISON OF DBSCAN AND K-MEANS CLUSTER ANALYSIS WITH PATH-ANOVA IN CLUSTERING WASTE MANAGEMENT BEHAVIOUR PATTERNS Zuhdi, Muhammad Rizal; Al Jauhar, Hafizh Syihabuddin; Fernandes, Adji Achmad Rinaldo; Wardhani, Ni Wayan Surya
Jurnal Teknik Informatika (Jutif) Vol. 6 No. 1 (2025): JUTIF Volume 6, Number 1, February 2025
Publisher : Informatika, Universitas Jenderal Soedirman

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.52436/1.jutif.2025.6.1.4183

Abstract

This study aims to compare the effectiveness of DBSCAN and K-Means cluster analysis methods in clustering waste management behaviour patterns in Batu City. The data used is secondary data from previous research with a total of 395 respondents taken using the quota sampling method. DBSCAN classifies data based on density with the main parameters epsilon and MinPts, while K-Means uses the average centroid to determine the cluster. The analysis results show that DBSCAN produces a silhouette index of 0.664, which is higher than K-Means with a value of 0.574. DBSCAN also successfully identified noise as much as 10 data that did not belong to any cluster, while K-Means did not have a similar mechanism. The results of Path-ANOVA show that DBSCAN is the most optimal clustering with a more significant partition difference value. Further tests were conducted to strengthen the validation of clustering results using Path-ANOVA. Both methods produced two main clusters, with the second cluster showing higher quality in terms of maintenance, quality, and ease of use of environmental hygiene facilities. This research emphasises the importance of choosing an appropriate clustering method to ensure optimal clustering results, especially in data with complex characteristics.
THE INFLUENCE OF MODERATING FACTORS IN STUNTING: LOGISTIC PATH ANALYSIS OF ORDINAL DATA Yulianto, Shalsa Amalia; Solimun, Solimun; Efendi, Achmad; Fernandes, Adji Achmad Rinaldo
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 19 No 2 (2025): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol19iss2pp1119-1132

Abstract

Logistic path analysis is used to analyze direct and indirect causal relationships between exogenous-endogenous variables with categorical data types. This study aims to apply logistic path analysis to ordinal categorical data and model the relationship between exogenous variables that affect nutritional status and physical status (stunting) in toddlers in Sumberputih Village, Wajak District. The data used is secondary data obtained from the results of filling out questionnaires in Sumberputih Village at the time of data collection in 2022-2023. The sample used in the study was 100 housewives who had toddlers. The sampling technique used was judgment sampling. However, the study only selected the variables of Birth Weight, Dietary Habits, Nutritional Status, and Physical Status (Stunting). The result of this study is that the variable of Birth Weight has a significant direct effect on Nutritional Status. The variable of Birth Weight has an indirect effect, and the total effect on Physical Status (Stunting) mediated by Nutritional Status is not significant. Meanwhile, the Diet variable has a significant direct effect on Physical Status. In addition, the Socioeconomic Condition variable can moderate the relationship between the Birth Weight variable and Physical Status. The diversity of data that can be explained by the model is 80.36%, while the rest is explained by other variables outside the model by 19.64%.
Integration Cluster and Path Analysis Based on Science Data in Revealing Stunting Incidents Marchamah, Mamlu’atul; Fernandes, Adji Achmad Rinaldo; Solimun; Wardhani, Ni Wayan Surya; Putri, Henida Ratna Ayu
Journal of Statistics and Data Science Vol. 1 No. 2 (2022)
Publisher : UNIB Press

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33369/jsds.v1i2.23570

Abstract

The purpose of this research is to utilize big data to explore the factors that influence the prevalence of stunting in Wajak Regency, model these factors using integrated cluster analysis and` path analysis model, and develop an information system for stunting incidence modeling. This study uses a descriptive and explanative approach, namely using Discourse Network Analysis, cluster analysis, path analysis, and integration of cluster and path analysis. The sample of this research is children under five in Wajak District who were selected using stratified random sampling. The distance measure that has the highest model goodness value in modeling using the integration of cluster analysis with path analysis is the Mahalanobis distance measure. The cluster analysis with Mahalanobis distance produces 3 clusters where cluster one is a toddler who has a low stunting category, cluster two is a group of toddlers who has a moderate stunting category, and cluster three is a group of toddlers who has a high stunting category. The originality of this study is the application of Discourse Network Analysis analysis to obtain new variables followed by a comparison of three distances namely euclidean, manhattan, and mahalanobis in modeling using cluster integration and parametric paths.
Considering Bali's Agricultural Policies in Implementing the Development of MDA-Path Analysis Rejeki, Sasi Wilujeng Sri; Solimun, Solimun; Nurjannah; Fernandes, Adji Achmad Rinaldo
JSMARTech: Journal of Smart Bioprospecting and Technology Vol. 6 No. 1 (2025): Vol. 6 No. 1 (2025): JSMARTech Volume 6, No 1, 2025
Publisher : JSMARTech

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21776/ub.jsmartech.2025.006.01.52

Abstract

The agricultural sector plays a vital role in Bali’s economy, culture, and food security, particularly in rice production. However, challenges such as land conversion and fluctuating farmer incomes have led the Bali government to implement various agricultural policies. Farmers' welfare is a critical factor in ensuring national food security, as prosperous farmers can improve production and maintain food stability. This study employs Discourse Network Analysis (DNA) to identify key factors affecting farmers' welfare in Bali and integrates MDA-Path Analysis to examine the relationships between exogenous variables and farmers' economic conditions. A mixed-method approach (qualitative and quantitative) is used to explore farmers' inclusivity and validate the MDA-Path Analysis model. Data is collected through in-sample validation using surveys conducted among farmers who are members of farmer groups in Bali. The results of this study indicate that human resource quality has the most significant impact on farmers' welfare, followed by price volatility and ease of technology use. The MDA-Path Analysis model demonstrates high classification accuracy, as reflected in sensitivity values exceeding 80%, confirming its effectiveness in distinguishing between different income and welfare categories. These findings provide valuable insights for strategic policy-making, enabling data-driven decision-making to enhance farmers' welfare and economic stability in Bali.
Regional Disparities in Public Expenditure Effectiveness; A Comparative Analysis of Western and Eastern Indonesia Sabir, Sabir; Rahman R, Abd; Fernandes, Adji Achmad Rinaldo; Bakar, Normizan bin
EcceS: Economics, Social, and Development Studies Vol 12 No 1 (2025): June
Publisher : Economics Department, Faculty of Economic and Islamic Business, Universitas Islam Negeri Alauddin Makassar, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study investigates the impact of government expenditure on employment across Indonesia’s regional economies, incorporating private investment as a mediating variable and region as a moderating variable. Using data from 2010 to 2022, the analysis focuses on five categories of government spending: general, housing and settlement, economic, education, and health. A multigroup path analysis model is employed to examine both direct and indirect effects of these expenditures on employment. The results reveal that government spending has a stronger impact on employment in the western region compared to the eastern region. Regional differences significantly moderate the relationship between government expenditure and private investment, particularly in general, economic, education, and health spending. In contrast, housing and settlement expenditure consistently affect both regions. Furthermore, private investment significantly enhances employment, especially in the western provinces. These findings underscore the importance of accounting for regional disparities in fiscal policy design and provide valuable insights for developing more effective and equitable regional economic strategies in Indonesia.
Structural Equation Modeling Semiparametric in Modeling the Accuracy of Payment Time for Customers of Credit Bank in Indonesia Junainto, Fachira Haneinanda; Fernandes, Adji Achmad Rinaldo; Solimun, Solimun; Hamdan, Rosita Binti
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 8, No 4 (2024): October
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v8i4.23668

Abstract

Credit risk assessment is crucial for financial institutions to ensure loan repayment. To enhance the prediction accuracy of creditworthiness and timely repayment, this research employs semiparametric structural equation modeling (SEM) to analyze the factors influencing credit repayment timeliness. The research was conducted to apply semiparametric SEM modeling to the timeliness of paying credit. Semiparametric SEM is structural modeling in which two combined approaches of parametric and nonparametric approaches are used. The analysis method in this research is semiparametric SEM with a nonparametric approach using a truncated spline. Truncated splines are chosen for their flexibility, ability to model complex relationships, continuity, interpretability, and strong performance in nonparametric regression tasks. The data in the study were obtained through questionnaires distributed to Bank X mortgage debtors and are confidential. The quetionnairs in the Likert scale, with five options. The study used 3 variables consisting of one exogenous variable, one intervening endogenous variable, and one endogenous variable. The results showed that: (1) the effect of capacity and willingness to pay variables on timeliness of payment is significant; (2) modeling the capacity variable on willingness to pay also produces a significant estimate; (3) the effect of the capacity variable on the timeliness of payment variable is not influenced by the willingness to pay variable as an intervening variable; and (4) the R^2 value of 0.763 or 76.33% indicates that the model has good predictive relevance. To continue to develop punctuality of paying credit, banks need to pay attention to the financial stability of consumers. Besides the financial stability, banks should pay attention to the sense of responsibility that customers have.
STRUCTURAL EQUATION MODELING MULTIGROUP INDIRECT EFFECTS ON BANK MORTGAGE PAYMENT TIMELINESS Maisaroh, Ulfah; Fernandes, Adji Achmad Rinaldo; Iriany, Atiek
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 17 No 4 (2023): BAREKENG: Journal of Mathematics and Its Applications
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol17iss4pp2359-2366

Abstract

Structural Equation Modeling (SEM) is a multivariate statistical method that is used to thoroughly explain the relationship between latent variables simultaneously. Until now, SEM continues to grow in research. This research was conducted to examine the indirect effect on the timeliness of paying bank mortgages with a multi-group moderation approach. Analysis to identify factors that influence the timeliness of paying bank mortgages is an important step for banks before extending credit to prospective customers. The data used in this research is secondary data from research grants from National Competitive Basic Research. The data scale used is the Likert scale for exogenous, mediating endogenous, and pure endogenous variables. While the moderating variable uses a dummy variable. The results of the study show that the indirect effect of Capacity and Capital on Pay on Time for Bank Mortgage customers has a significant effect, both on non-current collectibility status and current collectibility status. This is evidenced by the Sobel test value greater than (1.96) on the indirect effect test, and the p-value of the Wald test is smaller than (0.05) on the moderation indirect effect test. Mediator variable is able to increase the effect of exogenous variables on endogenous variable Customers with current collectibility status have a stronger influence on timely payments than customers with non-current collectibility status.
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