Generalized Poisson Regression Application to Model Factors Affecting the Number of New Diphtheria Cases in East Java Province in 2018
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Background: Diphtheria cases spread in almost all regions in Indonesia. In 2018 the highest number of diphtheria cases in East Java was 695 cases with a Case Fatality Rate (CFR) of 1.44%. Diphtheria is an acute infectious disease caused by Corynebacterium diphteriae bacteria. Environmental and behavior factors can be a cause of the spread of diphtheria.
Objectives: The purpose of the study was to apply the Generalized Poisson regression to identify the factors that influence of diphtheria cases in 2018.
Methods: The study used secondary data that had been published by the Provincial Health Office through data from the health profile of East Java Province in 2018. The population was a population in East Java Province in 2018 whose region consisted of 38 districts/cities. The sample in the study was diphtheria sufferers in East Java Province in 2018. The variable used in the study was the number of diphtheria cases as a dependent variable. The independent variable is the density of the population, the percentage of healthy homes, the percentage of households in a clean and healthy life behavior (CHLB), and the percentage of complete basic immunization. The data analysis used in the study is Generalized Poisson Regression
Result: The results of the study get the best model of diphtheria case = Exp [2,995+ 0.01381 (CHLB household)].
Conclusion: The conclusion of the study is a significant variable affecting the diphtheria case in East Java Province in 2018 is a CHLB household.
Afri, L. E. (2017). Perbandingan Regresi Binomial Negatif dan Regresi Conway-Maxwell-Poisson dalam Mengatasi Overdispersi pada Regresi Poisson. Jurnal Gantang, 2(1), 79–87. https://doi.org/10.31629/jg.v2i1.66
Agustini, R. D., Wahyuni, S., Buheli, K. L., & Suherlin, I. (2021). Determinan Pemberian ASI Eksklusif. Journal Midwifery Jurusan Kebidanan Politeknik Kesehatan Gorontalo, 7(1), 44. https://doi.org/10.52365/jm.v7i1.321
Arifin, I. F., & Prasasti, C. I. (2017). Factors That Related With Diptheria Cases of Children in Bangkalan Health Centers in 2016. Jurnal Berkala Epidemiologi, 5(1), 26. https://doi.org/10.20473/jbe.v5i1.2017.26-36
Arum, D. M. (2018). Pemodelan Faktor-Faktor yang Mempengaruhi Jumlah Kasus Difteri di Jawa Timur Tahun 2016 Menggunakan Generalized Poisson Regression. Retrieved from https://repository.its.ac.id/56511/
Dinas Kesehatan Propinsi JawaTimur. (2017). Profil Kesehatan Propinsi Jawa Timur 2017. Provinsi Jawa Timur, Dinkes, 34(11), e77–e77.
Dinkes. (2016). PROFIL KESEHATAN PROVINSI JAWA TIMUR TAHUN 2016 [East Java Health Profile 2016]. Provinsi Jawa Timur, Dinkes.
Dinkes Jatim. (2018). Profil Kesehatan Jawa Timur 2018. Dinas Kesehatan Provinsi Jawa Timur, 100. Retrieved from https://www.google.com/search?client=firefox-b-d&ei=zxpWXtieKq6c4-EPzvSfyAs&q=profil+kesehatan+jawa+timur+2018&oq=profil+kesehatan+jawa+timur+2018&gs_l=psy-ab.3..0i7i30l10.98332.105008..105951...0.4..0.1459.7810.2-1j0j2j2j2j3......0....1..gws-wiz.......0i
Evadianti, E., & Purhadi. (2014). Pemodelan Jumlah Kematian Ibu di Jawa Timur dengan Geographically Weighted Negative Binomial Regression (GWNBR). Jurnal Sains Dan Seni ITS, 3(2), 182–187.
Fadhillah, F. (2011). Aplikasi regresi binomial negatif dan.
Faidah, D. Y., & Pontoh, R. S. (2015). Pendekatan Hurdle Poisson Pada Excess Zero Data. Prosiding Seminar Nasional Matematika Dan Pendidikan Matematika, 131–136.
Harfika, M., Kuntoro, & Indawati, R. (2018). Pemodelan Regresi Linier Berganda untuk Estimasi Determinan Kasus Difteri di Jawa Timur. Health Event for All, PROSIDING, 89–100.
Ihsan, H., Sanusi, W., & Ulfadwiyanti, R. (2021). Model Generalized Poisson Regression (GPR) dan Penerapannya pada Angka Pengangguran bagi Penduduk Usia Kerja di Provinsi Sulawesi Selatan. Journal of Mathematics Computations and Statistics, 3(2), 109. https://doi.org/10.35580/jmathcos.v3i2.19190
Istiqomah, P. Z., Zinb, B., Kasus, P., Di, D., Jawa, P., Skripsi, T., ... Si, M. (2018). ABSTRAK Istiqomah, Rofiqoh, 2018,. 2–3
Izza, N., & Soenarnatalina, S. (2015). Analisis Data Spasial Penyakit Difteri di Provinsi Jawa Timur Tahun 2010 dan 2011. Buletin Penelitian Sistem Kesehatan, 18(2), 211–219.
Mardiana, D. E. (2018). The Influence of Immunization and Population Density to Diphtheria's Prevalence in East Java. Jurnal Berkala Epidemiologi, 6(2), 122. https://doi.org/10.20473/jbe.v6i22018.122-129
Masfian, I., Yuniarti, D., & Hayati, M. N. (2016). Penerapan Generalized Poisson Regression I Untuk Mengatasi Overdispersi Pada Regresi Poisson (Studi Kasus: Pemodelan Jumlah Kasus Kanker Serviks di Provinsi Kalimantan Timur). Jurnal Eksponensial, 7(1), 59–66.
Pontoh, R. S., & Faidah, D. Y. (2015). Penerapan Hurdle Negative Binomial pada Data Tersensor. Seminar Nasional Matematika Dan Pendidikan Matematika UNY, 117–122.
Pratiwi, F. M. (2018). Analisis Regresi Quasi Poisson Dan Regresi Generalized Poisson Untuk Menangani Data Overdispersi (Studi Kasus Data Banyaknya Kematian Bayi di Kabupaten Pasuruan Tahun 2013). Retrieved from http://repository.ub.ac.id/id/eprint/168390/
Putra, R., Wahyuning Tyas, S., & Fadhlurrahman, M. G. (2022). Geographically Weighted Regression with The Best Kernel Function on Open Unemployment Rate Data in East Java Province. Enthusiastic : International Journal of Applied Statistics and Data Science, 2(1), 26–36. https://doi.org/10.20885/enthusiastic.vol2.iss1.art4
Sriningsih, M., Hatidja, D., & Prang, J. D. (2018). Penanganan Multikolinearitas Dengan Menggunakan Analisis Regresi Komponen Utama Pada Kasus Impor Beras Di Provinsi Sulut. Jurnal Ilmiah Sains, 18(1), 18. https://doi.org/10.35799/jis.18.1.2018.19396
Yuliani, S., Budhiati. V., R., & Mashuri. (2016). Pemodelan Generalized Poisson Regression (GPR) Untuk Mengatasi Pelanggaran Equidispersi Pada Regresi Poisson Kasus Campak Di Kota Semarang Tahun 2013. UJM, 5(1), 40–46. Retrieved from https://journal.unnes.ac.id/sju/index.php/ujm/article/download/13103/7184
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