PENERAPAN REGRESI ZERO INFLATED GENERALIZED POISSON (ZIGP) PADA DATA OVERDISPERSION

  • NI WAYAN AMANDA DEWI SULISTYANINGSIH Udayana University
  • I KOMANG GDE SUKARSA Udayana University
  • NI LUH PUTU SUCIPTAWATI Udayana University

Abstract

Zero Inflated Generalized Poisson (ZIGP) is a regression model used to analyze Poisson distributed discrete data which contains mostly zero and tends to experience overdispersion (varians value greater than the mean value). The purpose of this research is to find out the best model and the factors which influence the maternal mortality in Bali Province in year 2016 by using ZIGP regression model. The data used in this research was data from health profile Bali Province with the object totally 57 district rate data has proportion of zeros value more than 50% on the response variable. The analysis result of ZIGP data on maternal mortality cannot modeled using the ZIGP so ZIGP regression model became ZIP model . The best model which resulted from ZIP regression got one free variable which have significant impact towards the total number of maternal mortality. This significant variabel is the percentage of mother did visiting to K1.   

Downloads

Download data is not yet available.

Author Biographies

NI WAYAN AMANDA DEWI SULISTYANINGSIH, Udayana University

Program Studi Matematika, Fakultas MIPA – Universitas Udayana

I KOMANG GDE SUKARSA, Udayana University

Program Studi Matematika, Fakultas MIPA – Universitas Udayana

NI LUH PUTU SUCIPTAWATI, Udayana University

Program Studi Matematika, Fakultas MIPA – Universitas Udayana

Published
2019-02-02
How to Cite
SULISTYANINGSIH, NI WAYAN AMANDA DEWI; SUKARSA, I KOMANG GDE; SUCIPTAWATI, NI LUH PUTU. PENERAPAN REGRESI ZERO INFLATED GENERALIZED POISSON (ZIGP) PADA DATA OVERDISPERSION. E-Jurnal Matematika, [S.l.], v. 8, n. 1, p. 1-8, feb. 2019. ISSN 2303-1751. Available at: <https://ojs.unud.ac.id/index.php/mtk/article/view/46506>. Date accessed: 21 nov. 2024. doi: https://doi.org/10.24843/MTK.2019.v08.i01.p228.
Section
Articles

Most read articles by the same author(s)

<< < 1 2