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Limits: Journal of Mathematics and Its Applications

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Published by Institut Teknologi Sepuluh Nopember Surabaya

ISSN : 1829605X EISSN : 25798936 DOI : -

Core Subject : Science, Education,

Computer Science & IT Mathematics

Limits: Journal of Mathematics and Its Applications merupakan jurnal yang diterbitkan oleh Pusat Publikasi Ilmiah LPPM Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia. Limits menerima makalah hasil riset di semua bidang Matematika, terutama bidang Analisis, Aljabar, Pemodelan Matematika, Sistem dan Kontrol, Matematika Diskrit dan Kombinatorik, Statistik dan Stokastik, Matematika Terapan, Optimasi, dan Ilmu Komputasi. Jurnal ini juga menerima makalah tentang survey literatur yang menstimulasi riset di bidang-bidang tersebut di atas.

Arjuna Subject : Matematika - Matematika Terapan

Articles 257 Documents

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Perbandingan Metode GWR, MGWR, dan MGWR-SAR pada Data Persentase Penduduk Miskin di Pulau Jawa Fahriya, Andina; Susetyo, Budi; Sumertajaya, I Made
Limits: Journal of Mathematics and Its Applications Vol. 22 No. 2 (2025): Limits: Journal of Mathematics and Its Applications Volume 22 Nomor 2 Edisi Ju
Publisher : Pusat Publikasi Ilmiah LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/limits.v22i2.3057

The primary goal of Sustainable Development Goals (SDGs) is to end poverty everywhere in all its forms. Poverty is defined as the inability to meet basic needs, such as food, clothing, shelter, education, and healthcare. In Indonesia, the poor population has reached 26.36 million people, with half of them residing on Java Island. Extensive research has been conducted on poverty, particularly using a spatial approach. Spatial regression is a statistical method that explicitly incorporates geographical aspects into a model framework. In spatial regression, two main challenges arise: spatial dependence and heterogeneity. These two effects are inherently interconnected and must be considered simultaneously. Mixed Geographically Weighted Regression with Spatial Autoregressive (MGWR-SAR) is a combination of Mixed Geographically Weighted Regression (MGWR) and Spatial Autoregressive (SAR). MGWR-SAR effectively addresses both spatial dependence and spatial heterogeneity simultaneously. This study aims to determine the best method for modeling the percentage of poor population on Java. The variables used included PPM, BPJSPBI, PPKM, PLSMP, PPTB, BPNT, NCPR, and IPM. The kernel function was selected based on the smallest cross-validation (CV) value, which was a Fixed Gaussian with a CV of 603.8268. Based on the GWR model, the global variables identified were PPTB, BPNT, and IPM, whereas the remaining variables were local. The MGWR-SAR method was found to be the best model for predicting the percentage of poor population, with an AIC = 448.9645, RMSE = 1.9075, and = 75.23%.

Pemodelan Angka Harapan Hidup Negara G7 dengan Pendekatan Analisis Regresi Data Longitudinal Farizi, Muhammad Fikry Al; Maula, Sugha Faiz Al; Fajrina, Sofia Andika Nur; Hilma, Dzuria Hilma Qurotu Ain; Suryono, Alda Fuadiyah; Chamidah, Nur
Limits: Journal of Mathematics and Its Applications Vol. 22 No. 1 (2025): Limits: Journal of Mathematics and Its Applications Volume 22 Nomor 1 Edisi Ma
Publisher : Pusat Publikasi Ilmiah LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/limits.v22i1.3368

Life expectancy is the average number of years of life a newborn baby will live in a given year. In general, life expectancy is a tool to evaluate government performance in improving community welfare. The aim of this research is prediction using longitudinal data regression analysis methods, namely Generalized Least Square with a Restricted Maximum Likelihood approach using a uniform correlation structure, Autoregressive (AR) (1), and Gaussian with factors that influence life expectancy, namely Tax to GDP ratio, Gross Domestic Product per Capita (GDPPC) and Health Expenditure per Capita from 2000-2020 in G7 countries. Based on the analysis results, it was found that tax revenues had a negative effect of 0.155 but the effect was not significant, GDP had a positive effect of 0.715 but had a significant effect, while health expenditure had a negative effect of 0.49 on Life Expectancy. The research results found that conditions in the G7 that were not ideal caused negative effects on taxes and health spending that were not in accordance with theory. The suggestions that can be given include tax reform from the source and its implementation, such as cigarette tax and sugary drink tax. In addition, it also provides suggestions to include universal health for a healthier and more prosperous society. This research is also in accordance with the aim of Sustainable Development Goals (SDGs) number 3, namely "Ensuring healthy lives and improving the welfare of all populations of all ages" and can be used as a policy reference for Indonesia.

Property Crime in Java Island 2022 based on Demography and Socioeconomic Aspects using Spatial Analysis Approach Vallessy, Fabian La Wima; Sirait, Timbang
Limits: Journal of Mathematics and Its Applications Vol. 22 No. 1 (2025): Limits: Journal of Mathematics and Its Applications Volume 22 Nomor 1 Edisi Ma
Publisher : Pusat Publikasi Ilmiah LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/limits.v22i1.3371

Property crime is the most common type of crime in Indonesia with the most rapid increasing in 2022. Java is the island with the highest magnitude of 65.85% if it is compared to the previous year and accounts for more than one third of the total cases in Indonesia. This study aims to determine an overview of these types of criminal offenses and the variables that affect them spatially. The analysis method uses in this study is descriptive analysis which will followed by inferential analysis, namely spatial analysis using Geographically Weighted Negative Binomial Regression (GWNBR). Based on this research, it is found that there are four regional groupings with variables that significantly affect all regions, namely life expectancy and Gini ratio. Meanwhile, there are variables that affect some regions, namely mean years schooling and total population. In addition, it is found that Geographically Weighted Negative Binomial Regression is better used than negative binomial regression in modeling property crime in Java Island in 2022.

Variables that Influence Urban Sprawl in DKI Jakarta, West Java and Banten Provinces in 2020 Khamila, Azzahra Dhisa; Sirait, Timbang
Limits: Journal of Mathematics and Its Applications Vol. 22 No. 1 (2025): Limits: Journal of Mathematics and Its Applications Volume 22 Nomor 1 Edisi Ma
Publisher : Pusat Publikasi Ilmiah LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/limits.v22i1.3372

DKI Jakarta, West Java and Banten provinces are the place of two large metropolitan areas in Indonesia that are interconnected. As a result, these areas have a high level of urbanization which can lead to urban sprawl. Urban Sprawl can cause various negative impacts, especially on the environment. Therefore, it is necessary to minimize urban sprawl, one of many ways is by analyzing the variables that affect urban sprawl. Several studies on spatial analysis of urban sprawl have been made extensively using satellite imagery data, one of them states that NDBI can capture patterns, characteristics and the causes of urban sprawl. However, research that utilizes NDBI as a variable approach for the urban sprawl has never been conducted in Indonesia. Therefore, this research was conducted with the aim of analyzing the effect of variables that indicated influence urban sprawl in the provinces of DKI Jakarta, West Java and Banten using spatial analysis. The results show that the average NDBI value is high in urban areas where the majority are in DKI Jakarta province. The variables that significantly influence urban sprawl are percentage of migrant population and tertiary sector of GRDP. By focusing on these variables, the government can make policies to minimize and control urban sprawl that occur in their area.

Analisis Survival Distribusi Lomax dengan Estimasi Maximum Likelihood Alexandra, Victoria Anggia; Prastyaningrum, Aprilia; Kurniawan, Ardi; Amelia, Dita
Limits: Journal of Mathematics and Its Applications Vol. 22 No. 1 (2025): Limits: Journal of Mathematics and Its Applications Volume 22 Nomor 1 Edisi Ma
Publisher : Pusat Publikasi Ilmiah LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/limits.v22i1.3373

Survival analysis is a statistical technique used to test the durability and reliability of a component. Life time data obtained from a life test experiment is often in the form of type III censored data, which occurs when observations enter at different times and last for varying durations. In survival analysis, data is expected to follow a certain probability distribution. To determine the characteristics of a population, a point estimate of the probability distribution parameters is conducted. This study aims to obtain parameter estimators of the Lomax distribution on type III censored data with the Maximum Likelihood Estimation (MLE) and Newton Raphson methods. Application of parameter estimation results on post-heart surgery survival data in one of the Jakarta hospitals. The result of estimating the parameter value in the post-heart surgery patient data is 1.552 and the result of estimating the parameter in the post-heart surgery patient data is 20.38. Based on these results, it can be concluded that the estimated probability of survival of a post-heart surgery patient for more than 49 days is 14.94%.

Perbandingan Metode Regresi Ridge dan Jackknife Ridge Regression pada Data Tingkat Pengangguran Terbuka Andini, Agita; Sunandi, Etis; Novianti, Pepi; Sriliana, Idhia; Agwil, Winalia
Limits: Journal of Mathematics and Its Applications Vol. 22 No. 1 (2025): Limits: Journal of Mathematics and Its Applications Volume 22 Nomor 1 Edisi Ma
Publisher : Pusat Publikasi Ilmiah LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/limits.v22i1.3374

Regression analysis is a statistical technique used to analyze the relationship between predictor and response variables. One of the parameter estimation methods commonly used for regression analysis is Ordinary Least Squares. This method produces unbiased and efficient estimates, known as BLUE (Best Linear Unbiased Estimator). In multiple linear regression analysis involving more than one predictor variable, it is essential to meet model assumptions such as the absence of multicollinearity. Multicollinearity is a condition where predictor variables have a high correlation, which can disrupt the stability of parameter estimates. Therefore, Ridge Regression and Jackknife Ridge Regression methods were used to address this issue. Both methods modify the least squares method by adding a bias constant value. This research uses the Open Unemployment Rate (OUR) data in Sumatra in 2022, and 3 predictor variables exhibit multicollinearity. Based on the analysis comparing the Mean Squared Error (MSE) values, the Jackknife Ridge Regression method yields the smallest MSE value, 0.004. Both methods are effective in addressing multicollinearity and identifying significant predictor variables for OUR in Sumatra Island, namely the Human Development Index (HDI), average years of schooling, number of poor people, Life Expectancy (LE), population density and inactive population

Model Regresi Gamma untuk Menganalisis Indeks Pengeluaran Kabupaten/Kota di Pulau Sumatra Otok, Bambang Widjanarko; Rini, Dyah Setyo; Fadhilah, Rahmi
Limits: Journal of Mathematics and Its Applications Vol. 22 No. 1 (2025): Limits: Journal of Mathematics and Its Applications Volume 22 Nomor 1 Edisi Ma
Publisher : Pusat Publikasi Ilmiah LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/limits.v22i1.3375

Gamma regression is part of Generalised Linear Models (GLMs) that can model data that is positive and asymmetric. The occurrence of data asymmetry is common in everyday life, for example in Human Development Index (HDI) data. The HDI has indicators called the Human Development Dimension Index, including the expenditure index, the education index and the life expectancy index. This study aims to model the expenditure index of districts/cities in Sumatra using Gamma regression because the expenditure index data is positive and non-symmetric. In modelling the Expenditure Index, the predictor variables used are the percentage of poor population, population density, percentage of population using their own toilet, and open unemployment rate in each district/city in Sumatra in 2023. The data used were obtained from the BPS website of the province corresponding to the regency/city in Sumatra. Based on the results of the analysis, all the predictor variables used had a significant effect on the expenditure index at the 1% and 5% significance levels, and the standard error value of each parameter estimate was small. In addition, the MSE of the model is also classified as small, which is 0.00163. This can prove that the model is supported by the data, although the coefficient of determination of the model ( ) in this study is only 47.59%.

Pembentukkan Tabel Morbiditas Penyakit Kronis Berdasarkan Angka Prevalensi Alim, Khairul; Kholijah, Gusmi; Meinarisa, Meinarisa
Limits: Journal of Mathematics and Its Applications Vol. 22 No. 1 (2025): Limits: Journal of Mathematics and Its Applications Volume 22 Nomor 1 Edisi Ma
Publisher : Pusat Publikasi Ilmiah LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/limits.v22i1.3377

A morbidity table is an important mathematical tool in health sciences and actuarial studies, providing an overview of disease rates in a population at a given time. This table offers information on the number of disease cases by age group, type of disease, or geographical region. The values from morbidity tables are used to compare disease rates between populations, evaluate the effectiveness of health programs, and predict future healthcare service needs. In the world of health insurance, morbidity tables play a crucial role in premium pricing calculations. By using specific morbidity tables, insurance providers can set premium prices that align with the conditions of the population being covered, preventing company losses due to premiums being set too low, while also ensuring that people do not feel burdened by excessively high premiums. Despite their importance, creating morbidity tables requires extensive research and large amounts of data. In Indonesia, accurately constructing morbidity tables is challenging due to its vast geographical diversity. Therefore, this study will use the prevalence rate of chronic diseases as an alternative. Prevalence rate is a statistical measure that describes the proportion of individuals in a population suffering from a specific disease at a given time. This approach simplifies data collection, especially since the government regularly releases prevalence data for certain diseases.

Pengaruh Suplementasi Vitamin D dan BMI terhadap LVEF dengan Pendekatan Generalized Additive Models Longitudinal Amelia, Dita; Suliyanto, Suliyanto; Alexandra, Victoria Anggia; Yosifa, Adelia Frielady; Rakhma , Syavrilia Alfiatur; Julianto, Agnes Happy
Limits: Journal of Mathematics and Its Applications Vol. 22 No. 1 (2025): Limits: Journal of Mathematics and Its Applications Volume 22 Nomor 1 Edisi Ma
Publisher : Pusat Publikasi Ilmiah LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/limits.v22i1.3378

Cardiovascular diseases (CVD) are the leading cause of global mortality, with Left Ventricular Ejection Fraction (LVEF) being a key indicator of heart function. This study explores the impact of vitamin D supplementation and Body Mass Index (BMI) on LVEF using Generalized Additive Models (GAM) in longitudinal data from 47 elderly patients with hypovitaminosis D undergoing orthopedic surgery. LVEF was measured before surgery and at 1, 3, and 6 months post-intervention. GAM was employed to capture nonlinear relationships between variables with working correlation structures such as Independence, Exchangeable, Unstructured, and Autoregressive-1 (AR-1). The findings revealed a significant increase in vitamin D levels and LVEF following supplementation, while BMI remained relatively stable throughout the observation period. The best GAM model with AR-1 correlation structure achieved the lowest Quasi Information Criterion (QIC) score of 443.47, indicating a complex relationship between vitamin D and LVEF and a linear relationship between BMI and LVEF. Vitamin D demonstrated a significant nonlinear effect on LVEF improvement, whereas a 1-point increase in BMI raised LVEF by 0.291%. This study underscores the importance of vitamin D supplementation in enhancing heart function among elderly patients with hypovitaminosis D, supporting the development of evidence-based health policies

Prediksi Harga Saham Big Four Banks di Indonesia Menggunakan Deret Fourier Multirespon Rasyid, Mochamad; Sediono, Sediono; Mardianto, M. Fariz Fadillah; Pusporani, Elly
Limits: Journal of Mathematics and Its Applications Vol. 22 No. 1 (2025): Limits: Journal of Mathematics and Its Applications Volume 22 Nomor 1 Edisi Ma
Publisher : Pusat Publikasi Ilmiah LPPM Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/limits.v22i1.3379

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Departemen Matematika Fakultas Sains dan Analitika Data Institut Teknologi Sepuluh Nopember Sukolilo, Surabaya 60111, Indonesia Phone: +62-31-5943354 Email: limits.matematika@its.ac.id

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Jawa timur

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Home Page

OAI Link

Editorial Team

Contact

Reviewer

Google Scholar

Contact Name Chairul Imron

Contact Email cha_imron15@its.ac.id

Phone +6285648721814

Journal Mail Official limits.matematika@its.ac.id

Editorial Address Departemen Matematika Fakultas Sains dan Analitika Data Institut Teknologi Sepuluh Nopember Sukolilo, Surabaya 60111, Indonesia Phone: +62-31-5943354 Email: limits.matematika@its.ac.id

Location Kota surabaya, Jawa timur INDONESIA

Abstract

Abstract

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Abstract

Abstract

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Abstract

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Abstract

Contact Name
Chairul Imron

Contact Email
cha_imron15@its.ac.id

Phone
+6285648721814

Journal Mail Official
limits.matematika@its.ac.id

Editorial Address
Departemen Matematika Fakultas Sains dan Analitika Data Institut Teknologi Sepuluh Nopember Sukolilo, Surabaya 60111, Indonesia Phone: +62-31-5943354 Email: limits.matematika@its.ac.id

Location
Kota surabaya,

Jawa timur

INDONESIA