PENERAPAN REGRESI ZERO INFLATED POISSON UNTUK MENGATASI OVERDISPERSI PADA REGRESI POISSON (Studi Kasus: Ketidaklulusan Siswa SMA/MA dalam Ujian Nasional di Buleleng)

LUH KOMANG MARDIANI (Faculty of Mathematics and Natural Sciences, Udayana University)
KOMANG GDE SUKARSA (Faculty of Mathematics and Natural Sciences, Udayana University)
I GUSTI AYU MADE SRINADI (Faculty of Mathematics and Natural Sciences, Udayana University)

E-Jurnal Matematika
Vol 2 No 3 (2013)

The Poisson regression analysis is one of the regression methods used for count data and has the assumption of equidispersion. However, it is the overdispersion and then underestimate standard errors will be obtained. If the data are overdispersed and more data is zero then ZIP (Zero Inflated Regression) regression is used. ZIP regression model is more appropriate to be used to analyze the amount of Senior High School/Madrasah Aliyah who do not pass the exam with five independent variables, because a lot of data failure is zero. In this paper, data are overdispersed on Poisson regression, so ZIP regression are used. ZIP regression models obtained are only influenced by the proportion of Senior High School/Madrasah Aliyah classroom were damaged (X3), is and .