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All Journal Hemera Zoa JURNAL MATEMATIKA STATISTIKA DAN KOMPUTASI Jurnal Agro Ekonomi JTSL (Jurnal Tanah dan Sumberdaya Lahan) Jurnal Agro Ekonomi Jurnal Pusat Inovasi Masyarakat Xplore: Journal of Statistics
Rahma Anisa
Department Of Statistics, IPB University, Bogor, Indonesia
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Decision Sciences, Operations Research & Management Engineering Environmental Science Mathematics Social Sciences

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PENDUGAAN FAKTOR – FAKTOR YANG MEMENGARUHI KASUS STUNTING DI JAWA BARAT TAHUN 2021 MENGGUNAKAN REGRESI SPASIAL BINOMIAL NEGATIF Anik Djuraidah; Mely Amelia; Rahma Anisa
Jurnal Matematika, Statistika dan Komputasi Vol. 20 No. 1 (2023): SEPTEMBER, 2023
Publisher : Department of Mathematics, Hasanuddin University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20956/j.v20i1.26984

Abstract

Stunting is a childhood growth and development disorder characterized by below-normal height.  West Java, with its stunting rate of 24.5 percent, is one of the provinces included in the top 12 priority provinces in implementing the National Action Plan to Accelerate Stunting. Stunting cases are count data and their occurrence is rare. The analysis for the count data is Poisson regression with the assumption that equidispersion must be met. One way to overcome overdispersion is to use negative binomial regression. This study aimed to determine predictors/factors affecting stunting cases in West Java province in 2021 using negative binomial spatial regression. The data in this study comes from the publication of the West Java Health Service and the West Java Central Statistics Agency in 2021 with districts/cities as the object of observation. There is a spatial effect in the stunting data, so the spatial regression model is suitable. The results show that there is an overdispersion in the Poisson regression. The spatial effect test shows that there is a spatial dependence on the response variable and some predictors. The negative spatial autoregressive binomial is the best model with the lowest AIC value. The factors that have a significant effect are the percentage of infants aged less than six months who are breastfed, the percentage of food processing establishments that meet the requirements, and the percentage of infants with low birth weight.
Co-Authors . Erfiani A.S. Satyaningtijas Aam Alamudi Abdullah Ilman Fahmi Aidi, Muhammad N Alina Witri Anang Kurnia Andhika Yudha Prawira Andhika Yudha Prawira Andhika Yudha Prawira Ani Safitri Anik Djuraidah Annisa Nur Hapsari Aurellia Layvieda Bagus Sartono Budi Susetyo Danang Dwi Cahyadi Desrayni Hanadhita Desrayni Hanadhita Desrayni Hanadhita Desrayni Hanadhita Dian Kusumaningrum Fahrizal Hazra Fajar Agus Pradana Haidar Muhammad Yasin Haryastuti, Rizqi HERA MAHESHWARI Herwin Pisestiyani I Made Sumertajaya Indonesian Journal of Statistics and Its Applications IJSA Latief Mahir Rachman Mely Amelia Muhammad N Aidi Muhammad Nur Aidi Nur Indah Andini Nur Laela Fitriani Pasaribu, Sahat M. Pika Silvianti Pika Silvianti Putu Gita Karlina Jayanti Qomsatun Istiqomah Rama Adi Rianto Rizqi Haryastuti Ryska Putri Madyasari Sahat M. Pasaribu Sandra Dewi Hartanti SATRIYAS ILYAS Savitri Novelina Srihadi Agungpriyono Supratikno . Sutomo, Valantino A Valantino A Sutomo Valantino Agus Sutomo Wulan Andriyani Pangestu Yani Nurhadryani