<![CDATA[Unpredictable rainfall can cause various negative impacts, especially in regions highly dependent on agriculture and infrastructure, such as Sleman Regency, Semarang, and Surabaya. Accurate weather predictions are crucial for anticipating disaster risks like floods, landslides, and droughts, as well as maintaining the sustainability of these vital sectors. This study aims to forecast rainfall in these three regions using the Autoregressive Integrated Moving Average (ARIMA) model. The ARIMA model was chosen for its flexibility in adapting to existing data patterns and its ability to provide accurate and economical predictions. Historical rainfall data from these three regions were analyzed using various ARIMA parameters (p, d, q) to identify the most optimal model. The results indicate that the ARIMA model can provide reasonably accurate rainfall predictions across all three regions with varying degrees of error. Significant differences were found in the model’s performance across the regions, influenced by local geographical and climatic characteristics.]]>
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