Article Per Year (5 Year)
p-Index From 2020 - 2025
1.152
P-Index
This Author published in this journals
All Journal JITRO (Jurnal Ilmiah dan Teknologi Peternakan Tropis) BAREKENG: Jurnal Ilmu Matematika dan Terapan Jurnal Abdi Masyarakat Saburai (JAMS) JURNAL ILMU MANAJEMEN SABURAI (JIMS) Science and Education Journal Mathematical Journal of Modelling and Forecasting Diophantine Journal of Mathematics and Its Applications
Reza Pahlepi, Reza
Halu Oleo University
Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Industrial & Manufacturing Engineering Mathematics Mechanical Engineering Physics Social Sciences Transportation Veterinary

Published : 7 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search
Journal : Mathematical Journal of Modelling and Forecasting

 1 
Modelling the Number of Stunting Cases in Indonesia in 2022 Using Negative Binomial Regression to Address Overdispersion Oktarina, Cinta Rizki; Pahlepi, Reza
Mathematical Journal of Modelling and Forecasting Vol. 2 No. 2 (2024): December 2024
Publisher : Universitas Negeri Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/mjmf.v2i2.27

Abstract

This study models the incidence of stunting in toddlers in Indonesia in 2022 using negative binomial regression to address the overdispersion issue often present in count data. The Poisson regression model, typically used for count data, showed less accurate results due to the variance exceeding the mean, indicating overdispersion. By adopting a negative binomial regression approach, this study accommodates higher variability in the data, leading to more accurate estimates. The results reveal that the percentage of pneumonia cases and low birth weight are significant factors in stunting incidence. In contrast, other variables, such as complete basic immunization and poverty levels, are insignificant in the final model. The final negative binomial model yielded a lower AIC value than the initial model, indicating an improved model fit, with an R-squared (Nagelkerke's R²) of 50.50%. This study offers enhanced insights into the factors influencing stunting, supporting more targeted health policy decisions to reduce stunting rates in Indonesia.
Co-Authors Aghnia, Haliza Agwil, Winalia Ahiruddin Ahiruddin Dewi, Ade Sandra Dian Agustina Enjelina, Tiara Husna Purnama Idhia Sriliana Kuswarak, Kuswarak Lies Kumara Dewi Mashuri, Faa’iz Nurul Hidayati Oktarina, Cinta Rizki Rauf, Eka Ubaya Taruna Rizki Oktarina, Cinta Sasora, Fajar Syuhada Putri, Sri Yanti, Rizki Dwi Yuliana Yamin