Article Per Year (5 Year)
p-Index From 2020 - 2025
0
P-Index
This Author published in this journals
All Journal Jurnal INKOM
Maria Ariesta
Krida Wacana Christian University
Computer Science & IT

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Web-Based Decision Support Systems Application of Stock Recommendation Using Bayesian Methods Nina Sevani; Maria Ariesta
INKOM Journal Vol 8, No 1 (2014)
Publisher : Pusat Penelitian Informatika - LIPI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/j.inkom.302

Abstract

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%.
Co-Authors Nina Sevani