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All Journal International Journal of Public Health Science (IJPHS) Media Statistika The Journal of Experimental Life Sciences (JELS) CAUCHY: Jurnal Matematika Murni dan Aplikasi Jurnal Mahasiswa Statistik Journal of Innovation and Applied Technology Jurnal Teknologi Informasi dan Ilmu Komputer Mutiara Medika: Jurnal Kedokteran dan Kesehatan Prosiding SI MaNIs (Seminar Nasional Integrasi Matematika dan Nilai-Nilai Islami) Jurnal Penelitian Pendidikan IPA (JPPIPA) JURNAL ILMIAH MATEMATIKA DAN TERAPAN BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) ComTech: Computer, Mathematics and Engineering Applications Industri Inovatif : Jurnal Teknik Industri Jambura Journal of Biomathematics (JJBM) Pakem : Jurnal Pengabdian Kepada Masyarakat
Henny Pramoedyo
Prodi Statistika Jurusan Matematika FMIPA Universitas Brawijaya
Agriculture, Biological Sciences & Forestry Arts Humanities Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Health Professions Immunology & microbiology Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Materials Science & Nanotechnology Mathematics Mechanical Engineering Medicine & Pharmacology Neuroscience Physics Public Health Social Sciences Transportation Other

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Geographically Weighted Poisson Regression Modeling Using Adaptive Gaussian Kernel Weighting For Mapping Maternal Mortality Rates In East Java Ngoro, Inayati; Pramoedyo, Henny; Astuti, Ani Budi
Jambura Journal of Biomathematics (JJBM) Volume 6, Issue 4: December 2025
Publisher : Department of Mathematics, Universitas Negeri Gorontalo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37905/jjbm.v6i4.30411

Abstract

Maternal Mortality Rate (MMR) is a key public health indicator that reflects spatial variation across districts in East Java.  This study aims to model the spatial distribution of MMR using Geographically Weighted Poisson Regression (GWPR) with an Adaptive Gaussian Kernel weighting function. Secondary data were obtained from the 2022 East Java Provincial Health Profile, covering 38 districts and municipalities. The results indicate that GWPR outperforms the classical Poisson regression. The intercept β=2.889 (exp=17.95) suggests an average of 18 maternal deaths in the absence of predictor effects. The coverage of the fourth antenatal care visit (K4) has a significant negative effect ( β=-0.027; exp = 0.973), indicating that a 1% increase in K4 coverage reduces MMR by approximately 2.7%. Conversely, obstetric complications managed by midwives show a significant positive effect (β= = 0.0173; exp = 1.017), meaning that a 1% increase in complications raises MMR by 1.7%. Other predictorsfirst antenatal care visit (K1), ironfolic acid (IFA) supplementation, and number of health workersare not statistically significant. This study underscores the importance of expanding K4 coverage and strengthening complication management as priority strategies to reduce maternal mortality.  Furthermore, GWPR-based mapping enables more targeted maternal health interventions tailored to local characteristics.
Geospatial patterns and determinants of toddler stunting: evidence from geographically weighted regression Anismuslim, Muhammad; Pramoedyo, Henny; Andarini, Sri; Sudarto, Sudarto
International Journal of Public Health Science (IJPHS) Vol 15, No 1: March 2026
Publisher : Intelektual Pustaka Media Utama

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijphs.v15i1.23216

Abstract

This study aimed to map and analyze the spatial distribution of toddler stunting in Malang and identify key risk factors that are spatially correlated with stunting incidence across sub-districts and villages. A geospatial modeling approach using geographically weighted regression (GWR) was employed to account for local variations in the influence of risk factors, reflecting the heterogeneity of conditions that contribute to stunting in different areas. The analysis revealed significant spatial autocorrelation, with stunting cases clustering in specific locations. Results indicate that sanitation risks and household waste management practices were the most significant determinants of stunting prevalence among toddlers in Malang. Improper waste segregation, which leads to odors and attracts flies, and ineffective disposal methods, such as open burning or dumping, were strongly associated with higher stunting rates. These findings underscore the importance of targeted interventions addressing environmental health and sanitation at the local level. By integrating geospatial analysis with GWR modeling, this study highlights the spatial heterogeneity of stunting determinants, providing evidence to guide community-specific public health strategies. Improved sanitation practices and proper household waste management are critical to reducing toddler stunting in areas with clustered risk.
Geographically and Temporally Weighted Regression Modeling in Analyzing Factors Affecting the Spread of Dengue Fever in Malang Indrayani, Fahmi; Pramoedyo, Henny; Iriany, Atiek
The Journal of Experimental Life Science Vol. 8 No. 2 (2018)
Publisher : Graduate School, Universitas Brawijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1175.267 KB) | DOI: 10.21776/ub.jels.2018.008.02.01

Abstract

Geographically and Temporally weighted regression (GTWR) modeling has been developed to evaluate spatial heterogeneity and temporal heterogeneity in factors influencing the spread of dengue fever in Malang city. By using the monthly data in 2012-2015 as the temporal unit of each urban village in Malang and village is considered as a spatial unit. GTWR model is compared with the GWR model using several statistical criteria. GTWR model shows that the relationship between dengue incidence with population density and monthly average temperature significantly affects each Village in Malang.Keywords : DHF, GTWR, Spatiotemporal Pattern
Co-Authors Achmad Efendi Alfi Fadliana Amelia, Okky Ariska Ani Budi Astuti Ani Budi Astuti Anismuslim, Muhammad Ardianti, Deby Arif, Nur Fitriyah Atiek Iriany Chairunissa, Abela Danang Ariyanto Eni Sumarminingsih Fachri Faisal Fernandes, Adji Achmad Fernandes, Adji Achmad Rinaldo Gani, Friansyah Handoyo, Samingun Heni Kusdarwati Indrayani, Fahmi Jaka Pratama Musashi Jannah, Friendtika Miftaqul Khoirunnisa, Elsa Azizah Korniasari, Leli Dwi Kurniawan, Galih Widhi Kusdarwati, Heni Liduina Asih Primandari, Liduina Asih Loekito Adi Soehono Luthfatul Amaliana, Luthfatul Maghfiroh, Aulia Maharani, Kasih Megasari, Dannys Melanwati, Rinda Lolita Mitakda, Maria Bernadetha Mudjiono Mudjiono, Mudjiono Ngoro, Inayati Ni Wayan Surya Wardhani Ni Wayan Surya Wardhani Novi Nur Aini, Novi Nur Nur Azizah Rahma Fitriani Ramadhan, Apry Zakaria Ramadhan, Rajuliaddin Ridwan, Yusrina Layli Riza, Sativandi Rizkiyani, Cirairina Sa’adah, Zumrotus Saniyawati, Fang You Dwi Ayu Shalu Saris, Laode Muhammad Sariyya, Hanah Rista Septiani, Kurniawati Setiarini, An Nisa Dwi Shara, Yoeniarti Siswahyudianto Sri Andarini Suci Astutik Sudarto Sudarto Sumarminingsih, Eni Suryawardhani, Ni Wayan Widya Reza Wigbertus Ngabu Wijaya, Dewi Ratnasari Yanuari, Anindita Yuli Triana, Eka Putri