MODEL OF TRANSFER FUNCTION IN SERIES TIME ANALYSIS TO PREDICT RAINFALL

This study aimed to model and predict rainfall in the city of Makassar using transfer function model in time series
analysis. Forecasting procedures performed by several stages, namely: identification, pre-whitening, the cross-correlation
calculation, weighting impulse response, determining the value (b, r, s) and row noise, parameter estimation, diagnostic testing
and forecasting. Data research using secondary data is data of rainfall and air temperature over 100 months Makassar city
modeled and estimated using the basic theory of time series analysis and the theory of transfer function model. The results
obtained by the data model of rainfall and air temperature using time series analysis model transfer function (b, r, s) as follows:
forecasting results rainfall data showed that the rainy season ended in the fifth month of the year and the dry season only
started in the sixth month of the year, while the next rainy season, or the end of the dry season will occur in the eleventh month
of the year.