Pemodelan Tingkat Inflasi di Sumatra Menggunakan Model Gamma dan Binomial Negatif
DOI:
https://doi.org/10.58192/ebismen.v3i4.2785Keywords:
Inflasi, Generalized Linear Models, Binomial Negatif, distribusi Gamma, SumateraAbstract
This study models the inflation rate in Sumatra using Generalized Linear Models (GLM) with Gamma and Negative Binomial distributions. The data includes inflation rates, Consumer Price Index (CPI), poverty rates, and employment sectors from the 2019 BPS report. The results show that the Gamma model performs better in predicting inflation compared to the Negative Binomial model, with a lower AIC value and smaller residual deviance. The CPI variable significantly influences inflation, while other variables are not significant.
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