Web-Based Decision Support Systems Application of Stock Recommendation Using Bayesian Methods

Nina Sevani (Krida Wacana Christian University)
Maria Ariesta (Krida Wacana Christian University)

Jurnal INKOM
Vol 8, No 1 (2014)

We propose an application that can support traders by providing recommendation about the right stock transaction. The expected impact from this application is to reduce the risk of loss, even achieve the maximum profit for traders who use this application. Recommendation that resulted by application is based on Bayesian methods calculation and four technical analysis indicators that most commonly used by stock experts, i.e. Bollinger Bands, Moving Average Convergence Divergence (MACD), Relative Strength Index (RSI), and Stochastic Oscillator. Methodology used in this paper consists of data collection, data analysisa, application design, implementation, and testing. From the results of application testing, the accuracy of the application is 87,37%.