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PENDEKATAN DATA TIME SERIES MENGGUNAKAN K-NEAREST NEIGHBOR BERBASIS PREPROCESING PADA PREDIKSI HARGA SAHAM

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Title PENDEKATAN DATA TIME SERIES MENGGUNAKAN K-NEAREST NEIGHBOR BERBASIS PREPROCESING PADA PREDIKSI HARGA SAHAM
 
Creator Aziz, Abdul
 
Description Forex Market is a type of trade or transactions of a country's currency to another country's currency (the currency pair / pair), which involves major money markets in the world for 24 hours continuously. A trader is required to have the ability of technical analysis and fundamental good to be able to reap huge profits. Analysis traders used to predict the price in the market will rise or fall based lower threshold price (support) and upper threshold price (resistance). This study used the method of K-Nearest Neighborand a Fibonacci retracement to predict support and resistance levels. The data used in this study downloaded from the server Forex Alpari UK which consists of open, high, low, close, and volume as input data. In this study, training data and testing using test data with different time intervals. This test resulted in an accuracy rate is 50.76% on the test using the training data and test data 2 years 1 month 4 hour period of real data.
 
Publisher Program Studi Teknik Informatika, Fakultas Teknik, Universitas Yudharta Pasuruan
 
Date 2015-06-26
 
Type info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
 
Format application/pdf
 
Identifier https://jurnal.yudharta.ac.id/v2/index.php/EXPLORE-IT/article/view/280
 
Source 2549-354X
2086-3489
 
Language ind
 
Relation https://jurnal.yudharta.ac.id/v2/index.php/EXPLORE-IT/article/view/280/200
 
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