<![CDATA[This research aims to study the periodic and stochastic modeling of daily precipitation data series. The study was carried out using data of daily rainfall data with a length of 13 years (1987 – 2000) from Pahoman, Sumur Putri, and Sumber Rejo rainfall stations. The rainfall series used is as- sumed to be free from the influence of the trend. This research use how to convert data into time series sepektrum rain precipitation using program FFT (Fast Fourier Transform). Periodicity of daily rainfall data is presented using a periodic component 512. Stochastic rainfall series of rain- fall data is assumed as the difference (error) between the rainfall data with periodic rainfall model using 512 components. Based on the data series on stochastic stochastic component, calculated using the approach of the autoregressive model. Stochastic models presented by using a autore- gressive model of order two. The results of this research is the value of the correlation coefficient of the average precipitation three stations. For this study, the average correlation coefficient (R) between data and model of 0,9719 is periodic, between data and stochastic model is 0,9974, and between the data and the model with stochastic is 0,9974. From these results it can be concluded that periodic stochastic model of the rainfall of the Bandar Lampung City that processing model using 512-series compo- nents, presented a very significant approach.]]>
