Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal Jurnal FASILKOM (teknologi inFormASi dan ILmu KOMputer)
iswanto
Institut Sains Terapan dan Teknologi Surabaya (ISTTS)
Computer Science & IT Decision Sciences, Operations Research & Management

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

Found 1 Documents
Search

 1 
APPLYING THE CLASSIFICATION ALGORITHM FOR THE SYSTEM RECOMMENDATIONS BUY SELL IN FOREX TRADING iswanto; Yuliana Melita Pranoto; Reddy Alexandro Harianto
JURNAL FASILKOM (teknologi inFormASi dan ILmu KOMputer) Vol 10 No 2 (2020): Jurnal Fasilkom
Publisher : Fakultas Ilmu Komputer, Unversitas Muhammadiyah Riau

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1152.596 KB) | DOI: 10.37859/jf.v10i2.2076

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
Co-Authors Reddy Alexandro Harianto Yuliana Melita Pranoto