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Windya Harieska Pramujati
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Journal : Inferensi

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Risk Analysis Forecasting Models of Poisson Regression, Negative Binomial Regression, Poisson GSARIMA, and Negative Binomial GSARIMA (Case Study: Number of Bicycle Sales) Pramujati, Windya Harieska
Inferensi Vol 7, No 2 (2024)
Publisher : Department of Statistics ITS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j27213862.v7i2.20255

Abstract

The Poisson model is a model that can be applied to count data, where in this research the case study used is the number of bicycle sales. However, there is an equidispersion assumption in the Poisson model, that the response variable has the same mean and variance. A more flexible model is needed if the equidispersion assumption is not met, namely the Negative Binomial model. In this research, two models were applied, namely the regression model and the GSARIMA model, with two different distributions, namely the Poisson distribution and the Negative Binomial distribution. Therefore the models that will be compared are the Poisson Regression, Negative Binomial Regression, Poisson GSARIMA, and Negative Binomial GSARIMA models. The differences in results for each model are due to errors that occur in each model used. Hence, a model with a smaller error can be said to be a model that has a smaller risk than other models. The results of this study show that the error rate in the Negative Binomial GSARIMA ZQ1 model is relatively smaller than other models with a value of AIC = 1058.7. This model is the best model that can be used as a forecasting model in the case of bicycle sales and can minimize the risk of error in a forecasting result.
Co-Authors Ahmad Aviv Mahmudi Ahmad Nasuha Aji, Nugroho Priyo Amanti, Dyah Lutfi Anggoro, Zidan Dwi Azizah, Nurifa Laksmitasari Buana, Arya Sula Cakra Fajar Sodiq Fiddina, Qori' Afiata Indra Prasetya Khoiron, Agus Ahmad Maskuri Maskuri Melfasari, Anisha Muhammad Tahwin Neni Purwati Nita Sari Nita Sari, Nita Prasetya, Aditya Eka Safitri, Egi Syakur Syakur Yuliyanti, Siti Nur Sikhah Arum