<![CDATA[This research are intended to study the periodic and stochastic modeling of daily rainfalls. The study was carried out using data of daily rainfall with a length of 16 years (1991 – 2006) from Podorejo, Fajar Esuk, and Panutan rainfall stations. The rainfall series used is assumed to be free of trend. In this research data series were converted into series of rainfall sepektrum using FFT (Fast Fourier Transform). Periodicity of daily rainfall data is presented using 253 periodic com- ponent. Stochastic rainfall series of rainfall data is assumed as the difference (error) between the rainfall data with periodic rainfall model using data length of 512 days. Based on the data series, stochastic component were calculated using the approach of the autoregressive model. Stochastic models presented here are by using an autoregressive model of third order. The results of this research is the value of the correlation coefficient of the three stations. For this study, the average correlation coefficient (R) between data and periodic model is about 0,9770, between data and stochastic model is 0,9979, and between the data and the periodic stochastic model is 0,99991. From these results, it can be concluded that periodic stochastic model of the rainfall from Pringsewu area that processing model using 253 components, presented a very sig- nificant approach.]]>
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