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All Journal Jurnal Riset Kesehatan Poltekkes Depkes Bandung Innovative: Journal Of Social Science Research
Muktiwijaya, Aldi Wilaga
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Humanities Biochemistry, Genetics & Molecular Biology Computer Science & IT Dentistry Health Professions Immunology & microbiology Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Nursing Public Health Other

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Journal : Jurnal Riset Kesehatan Poltekkes Depkes Bandung

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THE NEGATIVE BINOMIAL REGRESSION APPROACH IS MORE APPROPRIATE FOR IDENTIFYING TUBERCULOSIS RISK FACTORS (DATA ANALYSIS OF MADIUN AND PONOROGO DISTRICTS) Muktiwijaya, Aldi Wilaga; Nugraha, Jaka
JURNAL RISET KESEHATAN POLTEKKES DEPKES BANDUNG, Online ISSN 2579-8103 Vol 17 No 2 (2025): Jurnal Riset Kesehatan Poltekkes Depkes Bandung
Publisher : Poltekkes Kemenkes Bandung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.34011/juriskesbdg.v17i2.2878

Abstract

Tuberculosis is an infectious disease caused by the bacterium Mycobacterium Tuberculosis and remains a serious health problem in Indonesia, including in Madiun and Ponorogo Regencies. The trend of tuberculosis cases in these two regions has shown a significant increase since 2021, despite a previous decline. This study aims to identify the factors affecting the number of tuberculosis cases in both regencies and evaluate the most suitable analysis method between Poisson regression and Negative Binomial regression. The Negative Binomial regression model is used to address the issue of overdispersion, which occurs when the data variance is greater than the mean, leading to inaccuracies in using Poisson regression. The results show that in Madiun Regency, significant factors influencing the number of tuberculosis cases include high altitude, the population of productive age, and good sanitation access. Meanwhile, in Ponorogo Regency, significant factors affecting tuberculosis cases include high altitude, the population of productive age, and the number of healthcare workers. Model evaluation indicates that Negative Binomial regression is more appropriate than Poisson regression due to its ability to handle overdispersion.
Co-Authors Abdul Aziz, Hilmy Edy Widodo Hermawan, Rachmat Jaka Nugraha Papua, Oceano Alpheratza Yumna, Pradipa Arka