ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI STUNTING PADA BALITA DI KOTA GORONTALO MENGGUNAKAN REGRESI BINOMIAL NEGATIF

FAHREZAL ZUBEDI, MUFTIH ALWI ALIU, YOLANDA RAHIM, FRANKY ALFRITS OROH

Abstract


This study aims to model stunting cases in children under five in Gorontalo city in 2018. In this model, it can be seen that the significant factors that affect stunting cases in children under five in Gorontalo city in 2018.  This study uses data on stunting cases in 9 (nine) districts in the city of Gorontalo and the factors that influence it. The research data were obtained from the Public Health in Gorontalo city. This study used one response variable, namely the number of cases of stunting and four predictor variables, namely number of toddlers who received exclusive breastfeeding, the percentage of low birth weight (LBW), the percentage toddlers who received complete basic immunization, and number of proper sanitation. The results obtained were the variables of number of toddlers who received exclusive breastfeeding and the percentage toddlers who received complete basic immunization which had a significant effect on stunting cases in children under five in the city of Gorontalo in 2018. This was indicated by the P-value of the variable for number of toddlers who received exclusive breastfeeding of 0.00283 and P-value of variable the percentage toddlers who get complete basic immunization is 0.06564. 

Keywords


Stunting; Negatif Binomial Regression

Full Text:

PDF

References


Alan Agresti (2009), An introduction to categorical data analysis (2nd edn)., John Wiley & Sons, Inc., Hoboken, New Jersey. https://doi.org/10.1002/sim.3564.

Amaliana, L., Sa’adah, U., and Wardhani, N. W. S. (2018), “Performa Proporsi Zero-Inflation Pada Regresi Zero-Inflated Negative Binomial (Studi Kasus: Data Tetanus Neonatorum Di Jawa Timur),” E-Jurnal Matematika, 7, 41. https://doi.org/10.24843/mtk.2018.v07.i01.p183

.

Apriluana, G., and Fikawati, S. (2018), “Analisis Faktor-Faktor Risiko terhadap Kejadian Stunting pada Balita (0-59 Bulan) di Negara Berkembang dan Asia Tenggara,” Media Penelitian dan Pengembangan Kesehatan, 28, 247–256. https://doi.org/10.22435/mpk.v28i4.472.

Aulele, S. N. (2012), “Pemodelan Jumlah Kematian Bayi Di Provinsi Maluku Tahun 2010 Dengan Menggunakan Regresi Poisson,” BAREKENG: Jurnal Ilmu Matematika dan Terapan, 6, 23–27. https://doi.org/10.30598/barekengvol6iss2pp23-27.

Dhiya, A. Y. (2020), “Pemodelan Penderita Stroke dan Diabetes Melitus di Kota Padang dengan Model Regresi Logistik Biner Bivariat,” IX, 270–277.

Fitrial, N. H., and Fatikhurrizqi, A. (2021), “Pemodelan Jumlah Kasus Covid-19 Di Indonesia Dengan Pendekatan Regresi Poisson Dan Regresi Binomial Negatif,” Seminar Nasional Official Statistics, 2020, 65–72. https://doi.org/10.34123/semnasoffstat.v2020i1.465.

Herindrawati, A. Y., Latra, I. N., and Purhadi, P. (2017), “Pemodelan Regresi Poisson Inverse Gaussian Studi Kasus: Jumlah Kasus Baru HIV di Provinsi Jawa Tengah Tahun 2015,” Jurnal Sains dan Seni ITS, 6. https://doi.org/10.12962/j23373520.v6i1.22976.

Keswari, N. M. R., Sumarjaya, I. W., and Suciptawaty, N. L. P. (2014), “Perbandingan Regresi Binomial Negatif dan Regresi Generalisasi Poisson dalam Mengatasi Overdispersi (Studi Kasus: Jumlah Tenaga Kerja Usaha Pencetak Genteng di Br. Dukuh, Desa Pejaten),” E-Jurnal Matematika, 3, 107. https://doi.org/10.24843/mtk.2014.v03.i03.p072.

Mahfudhotin, M. (2020), “Regresi Generalized Poisson Untuk Memodelkan Jumlah Penderita Gizi Buruk Pada Balita di Surabaya,” Jambura Journal of Probability and Statistics, 1, 47–56. https://doi.org/10.34312/jjps.v1i1.6876.

Prahutama, A., Sudarno, Suparti, and Mukid, M. A. (2017), “Analisis Faktor-Faktor Yang Mempengaruhi Angka Kematian Bayi Di Jawa Tengah Menggunakan Regresi Generelized Poisson Dan Binomial Negatif,” Statistika, 5, 1–6.

Ramadhani, N., Yanuar, F., and Yozza, H. (2018), “Penerapan Regresi Poisson Generalized Poisson Regression Dalam Memodelkan Kasus Angka Kematian Ibu Di Sumatera Barat Tahun 2015,” Jurnal Matematika UNAND, 7, 112. https://doi.org/10.25077/jmu.7.2.112-117.2018.

Rochmad (2013), “Aplikasi Metode Newton-Raphson Untuk Menghampiri Solusi Persamaan Non Linear,” Jurnal MIPA, 36, 193–200.

Sauddin, A., Auliah, N. I., and Alwi, W. (2020), “Pemodelan Jumlah Kematian Ibu di Provinsi Sulawesi Selatan Menggunakan Regresi Binomial Negatif,” Jurnal MSA ( Matematika dan Statistika serta Aplikasinya ), 8, 42. https://doi.org/10.24252/msa.v8i2.17409.

Sma, S., Yang, S. M. K., Lulus, T., and Di, U. N. (2012), “Penerapan Regresi Poisson Untuk Mengetahui Faktor-Faktor Yang Memengaruhi Jumlah,” 1, 59–63.

Sundari, I. (2012), “Regresi Poisson dan Penerapannya Untuk Memodelkan Hubungan Usia dan Perilaku Merokok Terhadap Jumlah Kematian Penderita Penyakit Kanker Paru-Paru,” Jurnal Matematika UNAND, 1, 71. https://doi.org/10.25077/jmu.1.1.71-76.2012.

Utami, T. W. (2013), “Analisis regresi binomial negatif untuk mengatasi overdispersion regresi poisson pada kasus demam berdarah dengue,” Jurnal Statistika Universitas Muhammadiyah Semarang, 1, 0–6.




DOI: https://doi.org/10.34312/jjps.v2i1.10284

Refbacks

  • There are currently no refbacks.


Copyright (c) 2021 Jambura Journal of Probability and Statistics

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.


Editorial Office of Jambura Journal of Probability and Statistics:
 
Department of Statistics, 3rd Floor Faculty of Mathematics and Natural Sciences, Universitas Negeri Gorontalo
Jl. Prof. Dr. Ing. B.J Habibie, Tilongkabila Kabupaten Bone Bolango, 96119
Telp: +6285398740008 (Call/SMS/WA)
E-mail: redaksi.jjps@ung.ac.id