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Muthahharah, Isma
Universitas Patompo Makassar
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Library & Information Science Mathematics Mechanical Engineering Medicine & Pharmacology Physics Public Health Social Sciences Transportation Other

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Journal : Journal of Mathematics, Computation and Statistics (JMATHCOS)

 1 
Analisis Spasial Bayesian dengan Metode CAR Leroux (Studi Kasus: Stunting di Indonesia) Muthahharah, Isma; Mar’ah, Zakiyah
Journal of Mathematics, Computations and Statistics Vol. 7 No. 2 (2024): Volume 07 Nomor 02 (Oktober 2024)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v7i2.4203

Abstract

Stunting has become a problem that has received special attention and is an urgent priority for the international community. Stunting or chronic malnutrition is a nutritional problem caused by malnutrition from food that lasts for a long time. The purpose of this study is to map the relative risk (RR) of stunting cases in Indonesia. This type of research is quantitative research. The data used are stunting cases that occurred in 2023 in Indonesia. The method used is Spatial Bayesian with the CAR Leroux Method. The selection of the best model is based on model suitability criteria, such as Watanabe Akaike Information Criterion (WAIC) and Deviance Information Criterion (DIC). The results of the analysis show that the best model obtained in the RR model of stunting cases in Indonesia shows that the CAR Leroux model with a higher GI (0.1; 0.1) is suitable for modeling the growth rate pattern of confirmed stunting cases in Indonesia. The three provinces with the highest RR values ​​are West Sulawesi Province, West Kalimantan Province, and East Nusa Tenggara Province. While the three provinces with the lowest RR values ​​are DKI Jakarta Province, South Sumatra Province, and North Sulawesi Province.
Classification Poverty Levels in Indonesia Using Discriminant Analysis Muthahharah, Isma; Hafid, Hardianti
Journal of Mathematics, Computations and Statistics Vol. 8 No. 1 (2025): Volume 08 Nomor 01 (April 2025)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v8i1.6816

Abstract

Poverty is a complex global challenge affecting countries like Indonesia that seek to improve the welfare of their citizens. Although the number of Indonesia's poor has fluctuated over the past few years, the study shows a decline in 2022. Using Multivariate Discriminant Analysis, this study aims to classify poverty levels in Indonesian provinces. Previous findings highlighted the relationship between the poverty depth index and average and duration of schooling. Through the development of classification models, this research seeks to provide a better understanding of poverty factors and support more effective policymaking in combating poverty in various regions. Using secondary data from the Central Bureau of Statistics in 2022, this research is quantitative research that produces important insights for the formulation of poverty eradication policies and programs in Indonesia. The result is the low provincial group of 20 provinces only 10 provinces are correctly predicted, the remaining 10 are predicted in the high province group. The same thing happened in the high province group of 13 provinces, only 9 provinces were correctly predicted, while the remaining 4 were predicted in the low group.
The Impact of Malnutrition on Infant Mortality Rate in Indonesia: A Spline Regression Approach Muthahharah, Isma; Hidayat, Rahmat
Journal of Mathematics, Computations and Statistics Vol. 8 No. 2 (2025): Volume 08 Nomor 02 (Oktober 2025)
Publisher : Jurusan Matematika FMIPA UNM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35580/jmathcos.v8i2.9351

Abstract

The Infant Mortality Rate (IMR) in Indonesia is still an important index in assessing the quality of public health. One aspect that is thought to influence the high IMR is malnutrition. One of the objectives of this study is to analyze the relationship between malnutrition and IMR through a nonparametric spline regression approach. The data used in this study are secondary data obtained from the Central Statistics Agency in 2022 with the IMR variable as the dependent variable and the percentage of malnutrition as the independent variable. The spline regression model was chosen because it is able to capture the nonlinear relationship between the variables analyzed. Based on the research results that have been obtained, we can see that the best model is spline regression, namely by selecting three knot points, the coefficient of determination (R^2) value is 23,27%. However, this model still has limitations, such as violations of residual assumptions. Therefore, it is hoped that further research will add or select other variables that may be more relevant in order to improve the quality of the model.
Co-Authors Abdul Rahman Agusalim Juhari Aidid, Muhammad Kasim Alfiah Nurfadhilah AM Hindi Amran Amrullah, Nursinah Andi Syukriani Aslindawati, Nur Asmayani Asmayani BT Samsuddin, Yati Bungatang Bungatang Bungatang Bungatang Hapsan, Amran Hardianti Hafid Hariani Harjuna Hariani Harjuna Harjuna, Hariani Husain, Ahmad Inayanti Fatwa Islamiah, Farida Khaidarsyah Khaidarsyah Mar'ah, Zakiyah Mar’ah, Zakiyah Masyitah Meliyana, Sitti Meliyana R, S.Pd, M.Si, Sitti Masyitah Muhammad Isbar Pratama Nur Aslindawati Rahmat Hidayat Resmawan Resmawan Rusdianto Rusdianto Rusdianto Rusdi Rustam, Sitti Nail S. Sugianty Sapinah Sapinah Septiary Pratiwi, Kartika Sitti Masyitah Meliyana R. St. Habibah, St. Habibah Sutamrin, Sutamrin Syalsabila, Annisa Syamsinar Zakiyah Mar'ah Zakiyah Mar’ah