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Adnan Sauddin
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Jurnal Matematika dan Statistika serta Aplikasinya (Jurnal MSA)
Published by Universitas Islam Negeri Alauddin Makassar
ISSN : 2355038X     EISSN : 25500767     DOI : https://doi.org/10.24252/msa
Core Subject : Economy, Health, Science, Education, Social,
Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Environmental Science Mathematics Medicine & Pharmacology
The Jurnal MSA (Jurnal Matematika dan Statistika serta Aplikasinya) is a brand new on-line anonymously peer-reviewed journal interested in any aspect related to mathematics and statistics with their application. The Jurnal MSA is ready to receive manuscripts on all aspects concerning any aspect related to mathematics and statistics science with their application.
Arjuna Subject : Matematika - Matematika (Lain-Lain)
Articles 295 Documents
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Metode Interpolasi Linear dalam Analisis Suku Bunga Kredit Berdasarkan Pembayaran Angsuran: Studi Kasus Pembiayaan Mobil New Agya 1.2 E M/T Abidin, Nurwahidah; Sri Dewi Anugrawati; Asriani Hasan
Jurnal MSA (Matematika dan Statistika serta Aplikasinya) Vol 12 No 2 (2024): VOLUME 12 NO 2 TAHUN 2024
Publisher : Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/msa.v12i2.53985

Abstract

An interest rate is the price or amount of additional payment paid by the borrower to the lender. The interest rate is usually not shown in the loan instalment brochure. This study aims to analyse the effective interest rate of vehicle financing loans. The method used to determine the effective interest rate in this study is linear interpolation. The calculated interest rates are flat interest rates and effective interest rates. Determining the most profitable car financing alternative for customers can be seen from the lowest interest rate. This study analyses the case of New Agya 1.2 E M/T car price through Kalla Toyota Palopo branch and credit through Mandiri Utama Finance at the end of 2023. Based on the results of data processing using the linear interpolation method, it is found that the higher the instalment payment and the smaller the tenor offered, the lower the interest rate.
Analisis Forecasting Peserta KB Jenis Suntik dan Pil Di Kabupaten Sidenreng Rappang Dengan Metode Seasonal Autoregressive Moving Average (SARIMA) Ahmad Faiz; Andi Mariani; Wahidah Alwi
Jurnal MSA (Matematika dan Statistika serta Aplikasinya) Vol 12 No 2 (2024): VOLUME 12 NO 2 TAHUN 2024
Publisher : Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/msa.v12i2.54841

Abstract

This study aims to analyze the increasing demand for contraceptives, making forecasting necessary to anticipate future needs and prevent supply shortages. To support this program, an effective forecasting method is required to predict the number of family planning (FP) participants in the future. This study employs the SARIMA (Seasonal Autoregressive Integrated Moving Average) time series method to forecast the number of FP participants using injections and pills in Sidenreng Rappang Regency. The results show that the SARIMA (0,1,0)(0,1,1)12 model is the most suitable for injection-based FP participants, while the SARIMA (1,1,0)(0,1,1)12 model is used for pill-based FP participants. The forecast indicates a decline in the numiber of injection and pill FP participants from January 2024 to December 2025.
Grouping of Regencies/Cities In West Sumatra Province Based On Economic Development Indicators Using The Self-Organizing Maps (SOM) Algorithm Wiwil Dzil Izzatil; Chairina Wirdiastuti; Syafriandi
Jurnal MSA (Matematika dan Statistika serta Aplikasinya) Vol 13 No 2 (2025): VOLUME 13 NO 2, 2025
Publisher : Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/msa.v13i2.57741

Abstract

Economic development is an important aspect in improving the standard of living of the community. To measure economic development progress in a region, relevant indicators are needed, one of which is Gross Regional Domestic Product (GRDP) per capita. In West Sumatra Province, there are disparities in RDP per capita between regions. Therefore, clustering is necessary to assist local governments in determining development priorities, formulating more targeted development policies, and allocating resources efficiently. This study aims to cluster West Sumatra regions using the Self-Organizing Maps algorithm based on economic development indicators. The analysis results identified three clusters: Cluster 1 consists of 6 districts/cities categorized as having moderate economic development, Cluster 2 includes 7 districts/cities with high economic development, and Cluster 3 consists of 6 other districts/cities categorized as having low economic development.
An Analysis of Poverty Using the System-GMM Approach: Evidence from Dynamic Panel Data in East Nusa Tenggara Province Pandu, Marvin Jecson
Jurnal MSA (Matematika dan Statistika serta Aplikasinya) Vol 13 No 2 (2025): VOLUME 13 NO 2, 2025
Publisher : Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/msa.v13i2.59056

Abstract

This study focuses on the application of the System-Generalized Method of Moments (System-GMM) statistical approach to analyze the determinants of poverty in 22 districts/municipalities in East Nusa Tenggara Province (NTT) over the period 2015–2019. The GMM method is employed to address issues of endogeneity, heterogeneity, and data persistence that are commonly encountered in regional socio-economic studies. By utilizing internal instruments, this approach enables more valid and robust parameter estimation. The panel data, obtained from the Central Bureau of Statistics, includes variables such as the Human Development Index (HDI), Open Unemployment Rate (OUR), and electrification ratio. The estimation results show that HDI has a negative and significant effect on poverty, with short-term and long-term elasticities of -0.984 and -2.244, respectively. The OUR has a positive and significant effect on poverty, with elasticities of +0.016 (short-term) and +0.036 (long-term), while the electrification ratio also shows a negative and significant effect, with elasticities of -0.035 and -0.081. These findings affirm that the application of the System-GMM method provides a more accurate depiction of the causal relationships among the determinants and supports evidence-based policymaking for poverty alleviation in structurally challenged regions such as NTT.
Premium Estimation Using a Spliced Gamma-Gamma Distribution for Long-Tail Insurance Claims Simanjuntak, Erica Grace; Madonna, Nora; Hayati, Ma'rufah
Jurnal MSA (Matematika dan Statistika serta Aplikasinya) Vol 13 No 2 (2025): VOLUME 13 NO 2, 2025
Publisher : Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/msa.v13i2.60648

Abstract

Determining fair premiums that accurately reflect actual risks is a crucial element in insurance risk management, particularly when claim data exhibits long-tail characteristics that are challenging to model using a single distribution. This study aims to develop a premium estimation model using the spliced Gamma-Gamma distribution, which can capture the behavior of small to large claims more flexibly. This model is applied to a collective risk model framework, focusing on calculating the expected value and variance of aggregate claims as the basis for premium estimation. Premium estimation is conducted using three actuarial principles: the expected value principle, the variance principle, and the standard deviation principle. The research indicates that the standard deviation principle yields the most accurate premium estimation, as it accurately reflects the risk level while striking a balance between premium adequacy and affordability for policyholders. This approach considers both the expected loss and its volatility, making it more adaptive to extreme claim risks. This study demonstrates that claim modelling using splicing distributions, combined with volatility-based premium estimation principles, can be a practical and realistic approach to managing risk and estimating premiums more accurately.
Generalized Linear Mixed Model Tree (GLMM-Tree) for The Classification of Direct Cash Transfer Recipients in West Java Province Nawawi, M. Ichsan
Jurnal MSA (Matematika dan Statistika serta Aplikasinya) Vol 13 No 2 (2025): VOLUME 13 NO 2, 2025
Publisher : Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/msa.v13i2.62521

Abstract

Generalized Linear Mixed Model Tree (GLMM-Tree) is a statistical method that combines the concepts of decision tree and Generalized linear mixed model (GLMM). Here are some key advantages including Flexibility in Handling Different Types of Data, Incorporation of Random Effects, Handling of Non-linear Relationships, Interpretability, Variable Selection, Robustness to Outliers, Capturing Interactions, No Need for Parametric Assumptions. The purpose of this study is to compare the GLMM and GLMM-tree methods for the classification of direct cash transfer recipients in West Java with 25890 observations using the GLMM-tree method. Looking at the MSE and RMSE values, GLMM-tree is superior to GLMM for both training and testing data
Nonparametric Model For Poverty Data: The Effect of Internal Factors Using Multi-Predictor Spline Regression in Indonesia Ruliana; Hidayat, Rahmat; Hardianti Hafid; Sudarmin
Jurnal MSA (Matematika dan Statistika serta Aplikasinya) Vol 13 No 2 (2025): VOLUME 13 NO 2, 2025
Publisher : Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/msa.v13i2.60319

Abstract

Poverty, as a multidimensional issue affecting national welfare and development, is the main focus of this research. This study investigates the impact of demographic and educational factors on the percentage of the poor population in Indonesia using a nonparametric Spline regression approach. The variables studied include the average population growth rate, the availability of schools in villages, and school enrollment rates. The best model, selected based on the lowest Generalized Cross Validation (GCV) value (0.204) and a high coefficient of determination (94.67%) is a nonparametric Spline regression model with an optimal combination of knot points. The analysis shows that all three predictor variables significantly influence the poverty rate. The model also meets standard statistical assumptions. These findings highlight the vital role of education and demographic factors in addressing poverty, thus strengthening education and controlling population growth should be a priority in poverty alleviation policies in Indonesia.
Implementasi regresi binomial negatif dalam mengatasi overdispersi pada analisis determinan jumlah pengangguran di pulau Sulawesi tahun 2023 Erna; Ermawati; Wahidah Alwi; Sri Dewi Anugrawati
Jurnal MSA (Matematika dan Statistika serta Aplikasinya) Vol 13 No 2 (2025): VOLUME 13 NO 2, 2025
Publisher : Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/msa.v13i2.61738

Abstract

This study focuses on the implementation of negative binomial regression as a solution to overcome the problem of overdispersion in the analysis of determinants of unemployment on the island of Sulawesi in 2023. Unemployment is not only viewed as a statistical phenomenon or economic issue, but also as an important indicator that reflects social welfare and the success of development in a region. Sulawesi Island, with its growth in the agricultural and industrial sectors, faces serious challenges in reducing unemployment rates, which have the potential to cause regional disparities if not addressed appropriately. This study aims to develop an appropriate negative binomial regression model to overcome overdispersion and identify the main factors that influence the unemployment rate. The method used is negative binomial regression analysis of district/city unemployment data in Sulawesi Island, which is discrete and shows symptoms of overdispersion. With significant variables including population size, Human Development Index (HDI), and the number of job placement or fulfillment services. These three factors have been proven to have a significant effect on the number of unemployed people in Sulawesi Island in 2023.
Chromatic Number of the Corona Product of Complete Graph and Star Graph Asmarani, Mustika; Yulianti, Kartika; Mulyaning Asih, Endang Cahya
Jurnal MSA (Matematika dan Statistika serta Aplikasinya) Vol 13 No 2 (2025): VOLUME 13 NO 2, 2025
Publisher : Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/msa.v13i2.56235

Abstract

In this paper, we determine the chromatic number of the corona product of complete graph $K_n$ and star graph $K_{1,m}$. Determination of the chromatic numbers is done by observing patterns, constructing conjectures, and proving them formally. We found that the chromatic number of the corona product of complete graph $K_n$ and star graph $K_{1,m}$ is $\chi\left(K_n\odot K_{1,m}\right)=\left\{\begin{matrix}3,\ \ n=1,2\\n,\ n=3,4,\ldots,\ k\\\end{matrix}\right.$, and the chromatic number of the corona product of star graph $K_{1,m}$ and complete graph $K_n$ is $\chi\left(K_{1,m}\odot K_n\right)=n+1,\ n=1,2,\ldots,\ k$. Furthermore, using Matlab software, a program is created to visualize the coloring of the vertices based on the formula that has been obtained.
Robust Spatial Autoregressive (Robust SAR) Modeling in the Case of Poverty Percentage in West Java Novi, Yoli Marda; Tessy Octavia Mukhti; Zamahsary Martha
Jurnal MSA (Matematika dan Statistika serta Aplikasinya) Vol 13 No 2 (2025): VOLUME 13 NO 2, 2025
Publisher : Universitas Islam Negeri Alauddin Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24252/msa.v13i2.61818

Abstract

Poverty is a complex problem influenced by various economic and social factors, such as the open unemployment rate, the minimum wage, population density, and the school participation rate. This study aims to model the poverty rate in West Java Province by considering spatial effects and the existence of outliers through the application of Spatial Autoregressive (SAR) and Robust Spatial Autoregressive (Robust SAR) models. Based on the Lagrange Multiplier test, the SAR model is declared suitable for use. However, the presence of outliers in the data necessitated the use of a robust approach to obtain more accurate results. The analysis showed that the Robust SAR model had a coefficient of determination of 81.53%, higher than that of the SAR model at 77.48%, making it a better model for explaining variations in poverty levels. Of the four independent variables, only School Participation Rate had a significant effect in both models, where an increase in School Participation Rate contributed to a decrease in the poverty rate. This finding confirms the importance of investment in education as a strategic effort to reduce welfare inequality between regions in West Java.

Page 29 of 30 | Total Record : 295

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