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All Journal BAREKENG: Jurnal Ilmu Matematika dan Terapan Zeta - Math Journal METIK JURNAL Mandalika Mathematics and Educations Journal JAMBURA JOURNAL OF PROBABILITY AND STATISTICS Mathematics and Applications (MAp) Journal VARIANSI: Journal of Statistics and Its Application on Teaching and Research Journal of Research Applications in Community Services Eksponensial Mikailalsys Journal of Mathematics and Statistics
Fauziyah, Meirinda
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ESTIMATION OF GEOGRAPHICALLY WEIGHTED PANEL REGRESSION MODEL WITH BISQUARE KERNEL WEIGHTING FUNCTION ON PERCENTAGE OF STUNTING TODDLERS IN INDONESIA Asnita, Asnita; Sifriyani, Sifriyani; Fauziyah, Meirinda
BAREKENG: Jurnal Ilmu Matematika dan Terapan Vol 18 No 1 (2024): BAREKENG: Journal of Mathematics and Its Application
Publisher : PATTIMURA UNIVERSITY

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30598/barekengvol18iss1pp0383-0394

Abstract

Stunting is a condition of failure to thrive in children under five years old due to chronic malnutrition. Efforts that can be made to reduce the incidence of stunting in Indonesia are to identify factors that are thought to affect the incidence of stunting in Indonesia. The analysis methods used in this study are the global Fixed Effect Model (FEM) and the local Geographically Weighted Panel Regression (GWPR) model. FEM is a global regression model that assumes that each individual's model has a different intercept value. While GWPR is a local regression model from FEM that considers aspects of geographic location, by repeating data at each observation location, different times, and using spatial data. The weighting function used in this study is fixed bisquare and adaptive bisquare. This study aims to obtain a GWPR model on the percentage of stunting toddlers in Indonesia in 2019 until 2022 with independent variables, namely the percentage of children receiving exclusive breastfeeding , the percentage of households that have access to proper sanitation , the average per capita health expenditure of the population for a month , the average length of schooling for women , and the number of poor people . The variables are obtained from Statistics Indonesia (BPS) and Study of Indonesia’s Nutritional Status (SSGI). The results showed that the best weighting function, namely adaptive bisquare with a CV value of 264.80.
Pendampingan Desain Infografis dengan Statistika dan Sains Data Bagi Siswa/Siswi MAN 1 Kota Samarinda Muhammad Fathurahman; Dani, Andrea Tri Rian; Fauziyah, Meirinda; Darnah; Goenjatoro, Rito; Hayati, Memi Nor; Prangga, Surya; Siringoringo, Meiliyani; Oroh, Chiko Zet
Journal of Research Applications in Community Service Vol. 4 No. 3 (2025): Journal of Research Applications in Community Service
Publisher : Universitas Nahdlatul Ulama Sunan Giri Bojonegoro

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.32665/jarcoms.v4i3.5158

Abstract

Kegiatan pengabdian masyarakat ini bertujuan untuk memberikan pendampingan desain infografis yang mengintegrasikan ilmu statistika dan sains data serta meingkatkan literasi data bagi siswa dan siswi MAN 1 Kota Samarinda. Dalam era digital yang ditandai dengan kemudahan akses informasi, masih terdapat kekurangan pemahaman di kalangan siswa mengenai pemanfaatan teknologi, khususnya dalam desain infografis berbasis statistika dan sains data. Infografis merupakan alat yang efektif untuk menyajikan informasi secara visual yang membantu mempercepat pemahaman data kompleks menjadi lebih mudah dipahami. Aplikasi Canva dipilih sebagai platform dalam pendampingan ini karena kemudahan penggunaannya, yang memungkinkan siswa untuk berkreasi secara mandiri. Berdasarkan hasil tes awal, siswa belum memanfaatkan dengan optimal pengembangan ilmu data sains dalam pembuatan desain infografis. Oleh karena itu, kegiatan ini dirancang untuk memberikan pemahaman dan keterampilan praktis kepada peserta agar mereka dapat menggunakan teknologi visual dalam mengelola dan menyampaikan informasi berbasis data dengan lebih efektif dan inovatif. Melalui metode pengabdian ini, diharapkan terjadi peningkatan pemahaman dan keterampilan dalam penggunaan desain infografis serta pemanfaatan sains data literasi siswa yang dapat diterapkan dalam kegiatan belajar mengajar, terutama dalam pengolahan dan penyajian data statistik.
A Simulation Study of Interval Estimation in Nonparametric Regression Using the Truncated Spline Estimator Puspitasari, Melda; Dani, Andrea Tri Rian; Fauziyah, Meirinda
Mandalika Mathematics and Educations Journal Vol 7 No 3 (2025): Edisi September
Publisher : FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jm.v7i3.9625

Abstract

This study examines interval estimation in truncated spline nonparametric regression using simulated data. The study aims to determine the impact of sample size, variance, and knot points on the performance of the truncated spline estimator. The results show that as the sample size increases, both the Generalized Maximum Likelihood (GML) and Mean Square Error (MSE) values decrease, while the coefficient of determination increases. This study also reveals that increasing the variance leads to higher GML and MSE values, as well as a lower coefficient of determination. Furthermore, the truncated spline nonparametric regression model achieves optimal performance with three knot points. The results showed that the more knot points, the GML and MSE values will decrease, while the coefficient of determination increases. The results of this study show that the determination of sample size, variance, and knot points significantly affects the accuracy and efficiency of the truncated spline nonparametric regression model, allowing it to serve as a reference for applying truncated spline nonparametric regression more effectively to produce a more optimal model that aligns with the characteristics of the data.
A District/City Profiling Based on Poverty Indicators in East Nusa Tenggara Using the Centroid Linkage Algorithm Dani, Andrea Tri Rian; Candra, Yossy; Putra, Fachrian Bimantoro; Fauziyah, Meirinda
Zeta - Math Journal Vol 10 No 2 (2025): November
Publisher : Universitas Islam Madura

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31102/zeta.2025.10.2.81-91

Abstract

Poverty is a complex multidimensional phenomenon that significantly impacts human life. Poverty has always been a problem that the government has discussed regionally, centrally, and internationally. The issue of poverty is interesting to approach and analyze using a statistical approach, namely cluster analysis. Cluster analysis is used to group objects based on their level of similarity. In this research, the algorithm used is the Centroid Linkage Algorithm. The Centroid Linkage algorithm was chosen based on its advantages in the grouping process. Distance similarity measurement uses Squared Euclidean. The data used are district/city poverty indicators in East Nusa Tenggara Province. The analysis results show that two optimal clusters were obtained with their distinguishing characteristics. Hopefully, the results of this analysis can be used as a reference in formulating policies for alleviating poverty.
Pemodelan Kadar Hemoglobin pada Pasien Demam Berdarah di Kota Samarinda Menggunakan Regresi Semiparametrik Spline Truncated Dani, Andrea Tri Rian; Putra, Fachrian Bimantoro; Zen, Muhammad Aldani; Sifriyani, Sifriyani; Fauziyah, Meirinda; Ratnasari, Vita; Adrianingsih, Narita Yuri
Jambura Journal of Probability and Statistics Vol 4, No 2 (2023): Jambura Journal Of Probability and Statistics
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjps.v4i2.18923

Abstract

This article discusses the innovation of statistical modeling in regression analysis with a semiparametric approach applied to health data. Regression analysis is a method in statistics that takes a lot of roles in statistical modeling. Regression analysis is used to model the relationship between the independent variable (x) and the dependent variable (y). There are three approaches to regression analysis, namely parametric, nonparametric, and a combination of the two, namely semiparametric. Semiparametric regression is used when the dependent variable has a known relationship with some of the independent variables and has an unknown pattern of a relationship with some of the other independent variables. The purpose of this study was to model hemoglobin levels in dengue fever patients, with the independent variables used being the number of hematocrits (x1) and the number of leukocytes (x2). The method used is spline truncated semiparametric regression. The truncated spline estimator was chosen for the nonparametric component because it has many advantages in modeling, one of which is being able to model patterns where the form of the relationship is unknown. The parameter estimation used is the maximum estimation. Selection of the optimal knot point using Generalized Cross-Validation (GCV). Based on the results of the analysis, the truncated spline semiparametric regression model was obtained which was applied to the hemoglobin level data in a model with three knots which have a coefficient of determination of 89.074%. Based on the results of testing the hypothesis simultaneously, it can be concluded that simultaneously the independent variable has a significant effect on the dependent variable. In the partial test, it is concluded that the variables x1 and x2 have a significant influence on the dependent variable y .
Co-Authors A'yun, Qonita Qurrota Asnita, Asnita Avrilia, Khairunnisa Budi, Ennesya Estya Candra Dewi, Ni Luh Ayu Candra, Yossy Dani, Andrea Tri Rian Darnah Darnah, Darnah Dimas Nugroho Dwi Seputro Goenjatoro, Rito Hadisti, Zahrah Dhafina Hadistii, Zahrah Dhafiinia Hardina Sandariria Koirudin, Hadi M. Fathurahman Marsandy, Aldwin Falah Hasan Mar’ah, Zakiyah Memi Nor Hayati NARITA YURI ADRIANINGSIH Oroh, Chiko Zet Puspitasari, Melda Putra, Fachrian Bimantoro Sifriyani, Sifriyani Siringoringo, Meiliyani Sri Wigantono Surya Prangga Vita Ratnasari Watika, Noor Hikmah Zen, Muhammad Aldani