<![CDATA[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.]]>
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