Every investor who transact in the capital markets hope benefits. But the stock has characteristics ofhigh risk-high return, it means that stocks allows investors to make a profit (capital gain) in largequantities in a short time, but it can also make stock investors suffered heavy losses in a short time.Investors require a number of methods in an effort to assist the purchase of shares of investmentdecision.Data of Stock price is a time series of data in a given period has a unique pattern. Then using machinelearning methods, this research is reviewing the use of SVM and MLP-related objects in PT MustikaRatu. Input variable is in the form of historical stock prices from 2007 to 2013. This study tried toreveal the level of RMSE (Root Mean Square Error) between SVM and MLP. Concluded that themethod of learning by using the MLP has a lower RMSE than using SVM.
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