<![CDATA[Changes in rainfall patterns caused by climate variability and global climate change have significant implications for water resource management and the increasing risk of hydrometeorological disasters. Therefore, rainfall trend analysis is essential to support regional planning and disaster mitigation efforts. This study aims to analyze the characteristics of monthly rainfall, identify rainfall trends using the Mann–Kendall test and Sen's Slope Estimator, and evaluate the relationship between rainfall and the number of rainy days using Pearson correlation analysis. A quantitative approach with a descriptive-analytical design was employed using secondary data obtained from the Statistics Indonesia (BPS) of West Java Province, based on observations from the Bogor Climatological Station during the 2019–2022 period, comprising a total of 48 monthly observations. Descriptive statistical analysis showed that the average monthly rainfall was 285.47 mm, while the average number of rainy days was 18.23 days per month. The Mann–Kendall test indicated that the rainfall trend was not statistically significant (p = 0.2516), although Sen's Slope Estimator suggested a slight increasing trend of 1.5675 mm per observation period. Furthermore, the Pearson correlation analysis revealed a moderate positive relationship between rainfall and the number of rainy days (r = 0.4646; p = 0.0009). These findings indicate that rainfall patterns in the Bogor region remained relatively stable during the study period, although increases in rainfall tended to be accompanied by an increase in the number of rainy days. The results are expected to serve as a scientific reference for water resource management, drainage system planning, and hydrometeorological disaster mitigation in the Bogor region.]]>
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