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All Journal JTAM (Jurnal Teori dan Aplikasi Matematika) EIGEN MATHEMATICS JOURNAL
Revika Inta Nur Kholifah
Department of Statistics, Universitas Muhammadiyah Semarang
Mathematics

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Modeling Inflation and Rupiah Exchange Rate Responses Using Bootstrap Aggregating Multivariate Adaptive Regression Spline in Indonesia Revika Inta Nur Kholifah; Tiani Wahyu Utami; Ali Imron
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 10, No 3 (2026): July
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v10i3.37314

Abstract

This study aims to evaluate the performance of the Bootstrap Aggregating (Bagging) method applied to Multivariate Adaptive Regression Splines (MARS) in improving the predictive ability of biresponse models, compared to biresponse MARS models without bagging, using a case study of inflation and the rupiah exchange rate in Indonesia. Inflation and exchange rates are important macroeconomic indicators that are interrelated and play a crucial role in maintaining economic stability; therefore, a prediction model capable of accurately capturing simultaneous relationships and nonlinear patterns is required. The contribution of this study lies in the application of a biresponse nonparametric regression framework based on bagging to simultaneously model biresponse variables, which has rarely been explored in previous research that generally focuses on a single-response approach. The biresponse approach is used to accommodate the interrelationship between response variables, while the bagging procedure is implemented through a bootstrap technique with several replication scenarios to reduce prediction variance and improve model stability. The final prediction is obtained by averaging the results from all bootstrap models formed. The results of this study indicate that the application of Bagging MARS with 100 replications can significantly improve model performance, as shown by a decrease in the RMSE value from 132.40 to 92.08 and MAE from 70.71 to 52.12, as well as an increase in the R² value from 0.9997096 to 0.9998597. These findings indicate that the integration of the bootstrap technique in the Bagging MARS approach is effective in reducing model variability and producing more stable predictions. Practically, the Bagging MARS method has the potential to be used as an alternative in modeling interrelated macroeconomic indicators with nonlinear characteristics.
Survival Analysis Using Kaplan-Meier and Cox Regression in Hypertension Patients at Kefamenanu Regional Hospital Muhammad Alvaro Khikman; Riska Multiyaningrum; Revika Inta Nur Kholifah; Lydia Nur Sa'adah; Elfina Latifah Safira; Albertus Dion Sarah; Ihsan Fathoni Amri; M. Al Haris
Eigen Mathematics Journal Vol 8 No 2 (2025): December
Publisher : University of Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/emj.v8i2.270

Abstract

Hypertension is a chronic disease with a steadily increasing global prevalence and is one of the leading causes of serious complications. Indonesia is among the countries with a high prevalence of hypertension, necessitating an understanding of the factors influencing patient treatment duration to enhance the effectiveness of healthcare services. This study aims to analyze differences in the survival rates of hypertensive patients at Kefamenanu Hospital based on gender. The Kaplan-Meier method was used to estimate patient survival rates, while Cox Proportional Hazards regression was used to evaluate the influence of gender on survival time. The Kaplan-Meier analysis results showed that female patients had a higher probability of survival than male patients during hospitalization. However, the Cox Proportional Hazards regression analysis indicated that this difference was not statistically significant. These findings suggest that while there are differences in survival patterns, gender is not the primary determinant of the duration of care for hypertensive patients. The results of this study are expected to provide input for hospitals in designing more effective care strategies that focus on other factors that may influence patient survival time.
Co-Authors Albertus Dion Sarah Ali Imron Elfina Latifah Safira Ihsan Fathoni Amri Lydia Nur Sa'adah M. Al Haris Muhammad Alvaro Khikman Riska Multiyaningrum Tiani Wahyu Utami