• Kusni Rohani Rumahorbo Badan Pusat Statistik Kabupaten Aceh Tengah, Indonesia
  • Budi Susetyo Department of Statistics, IPB University, Indonesia
  • Kusman Sadik Department of Statistics, IPB University, Indonesia



zero-inflated, hurdle, CZINB, CHNB, unhealthy-days


Health is a very important thing for humanity. One way to look at a person's health condition is through the number of unhealthy days which can also shows the productivity of the community in a region. Modeling the number of unhealthy days which are examples of count data can be done using Poisson regression. Problems that are often faced in data counts are overdispersion and excess zero. Poisson regression cannot be applied to data that experiences both of these. Zero Inflated Negative Binomial and Hurdle Negative Binomial modeling was performed on data with 2 conditions, uncensored and censored. The explanatory variables used are gender, age, marital status, education level, home ownership status and rural-urban status. According to the results of the AIC and RMSE calculation, Zero Inflated Negative Binomial on censored data showed the best performance for estimating the number of unhealthy days.


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How to Cite

Rumahorbo, K. R., Susetyo, B., & Sadik, K. (2019). PEMODELAN DATA TERSENSOR KANAN MENGGUNAKAN ZERO INFLATED NEGATIVE BINOMIAL DAN HURDLE NEGATIVE BINOMIAL. Indonesian Journal of Statistics and Its Applications, 3(2), 184–201.