<![CDATA[The rain is a natural phenomenon that is still a concern for several parties. Especially the assessment of rainfall in an area. This is important because high rainfall will result in natural disasters and have an impact on people's lives. So it is necessary to predict rainfall, although this is a complex problem. This research aims to optimise the prediction of Padang city rainfall data with monthly data for the period January 2018 to December 2021. The ARIMA model is used to analyse the data provided that the data must be stationary. Data stationarity can be seen from the Augmented Dickey-Fuller (ADF) test. After the ADF test is performed, the Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF) plots help in determining the order of the ARIMA model. The ARIMA (0,1,1) model was found to be the best model based on the smallest Akaike's Information Criterion (AIC) value.]]>
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