APPLYING THE CLASSIFICATION ALGORITHM FOR THE SYSTEM RECOMMENDATIONS BUY SELL IN FOREX TRADING

Abstract

Abstract- Having a sophisticated application, even though often experience problems in deciding BUY - SELL in trading forex trading. This is due to the often time series predictions, in the high variable experiencing high values ​​as well as low variables, for that it is needed a recommendation system to overcome this problem.
 The application of classification algorithms to the recommendation system in support of BUY-SELL decisions is one appropriate alternative to overcome this. K-Nearest Neighbor (K-NN) algorithm was chosen because the K-NN method is an algorithm that can be used in building a recommendation system that can classify data based on the closest distance. This system is designed to assist traders in making BUY-SELL decisions, based on predictive data.
 The results of the recommendation system from the ten trials predicted by Arima are recommended. When compared to the price in the field the target profit is 7% per week from ten experiments if the average profit has exceeded the target