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All Journal Jurnal TAMBORA Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika Berdikari : Jurnal Ekonomi dan Statistik Indonesia Jurnal Bayesian : Jurnal Ilmiah Statistika dan Ekonometrika PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON DATA SCIENCE AND OFFICIAL STATISTICS
Ade Marsinta Arsani
BPS-Statistics Indonesia
Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Industrial & Manufacturing Engineering Mathematics

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Journal : Jurnal TAMBORA

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ALTERNATIVE MODELS IN OVERCOMING THE PROBLEM OF OVERDISPERSION IN POISSON REGRESSION Pardomuan Robinson Sihombing; Ade Marsinta Arsani; Ni Komang Semara Yanti; Putu Pande Wahyu Diatmika
Jurnal TAMBORA Vol. 7 No. 2 (2023): EDISI 19
Publisher : Wakil Rektor 3, Direktorat Riset, Publikasi dan Inovasi, Universitas Teknologi Sumbawa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36761/jt.v7i2.2773

Abstract

This study aims to compare various alternative models in overcoming the problem of overdispersion in Poisson regression modeling. The comparative modeling is the Generalized Poisson model, Negative Binomial, and Generalized Negative Binomial. Modeling is applied to modeling the number of poor people in Central Java in 2021 with unemployment, HDI, and GRDP as independent variables. The results obtained by Generalized Poison are better than Negative Binomial and Generalized Negative Binomial because of the smaller AIC and BIC values ??and the larger R2. For simultaneous tests, it can be concluded that unemployment, HDI, and GRDP significantly affect the number of poor people. Only unemployment and HDI variables partially affect the number of poor people in Central Java. On the other hand, there is not enough evidence that GRDP affects some poor people. There is a need for comprehensive and relevant policies to overcome the number of poor people in an area.
Co-Authors Abdul Gofur Rochman Artha Satwika Chaoqing Huang Dyah Purwanti I Gede Heprin Prayasta I Gede Heprin Prayasta Ida Ayu Candrawati Ida Ayu Candrawati Mohamad Arif Kurniawan Nurhidayati Nurhidayati Pardomuan Robinson Sihombing Putu Pande Wahyu Diatmika Sigit Budiantono Sigit Budiantono Sigit Budiantono Triana Mauliasih Aritonang Widdia Angraini Wisnu Pratiko Yanti, Ni Komang Semara