| dc.description.abstract | Cash flow is a form of financial report that is used as a measure of the
company success in the investment world. So that companies need to forecast the
cash flow to manage their finances. Statistics can be applied for the forecasting of
cash flow using the Support Vector Machine (SVM) method on the time series data.
The aim of this research is to determine the optimal parameter pair model of the
Radial Basic Function kernel and to obtain the forecasting results of cash flow using
the SVM method on the time series data. The independent variable is needed the
data on cash flow from operating income, expenditure and investment expenditure,
sum of all cash flow. While the dependent variable is the financial condition based
on the Free Cash Flow. The result of this research is a model with the best
parameter pairs of the SVM tuning results with the greatest accuracy that is 75%,
82%, 88%, 64% and the forecasting financial condition of PT Cakrawala for the next
16 months. | en_US |
