Jurnal Teknologi Informasi dan Multimedia
Vol 1 No 3 (2019): November

Prediksi Harga Terendah Dan Harga Tertinggi Dengan Menggunakan Metode Anfis Untuk Analisa Teknikal Pada Forex Market

Moch. Lutfi (Universitas Yudharta Pasuruan)



Article Info

Publish Date
11 Nov 2019

Abstract

Forex Market Is a type of currency trading of the country that handles the world currency market within 24 hours agreed, foreign exchange trading has become an alternative for investors to save more trades in general and traders are required to support good technical analysis of good fundamentals so that able to reap huge profits. Technical analysis is an analysis used to estimate prices will fall at the lower price threshold (support) and the upper price threshold (resistance). Fibonacci Retracement is a method often used for technical analysis of rising prices or rising prices. The data used in this study was downloaded from the FBS Forex Market server which consists of open, high, low, close, and volume data. The next step is grouping data as a preprocessing method with the k-means method to normalize the data before the data is processed in the proposed method, the k-means method is a method of grouping data based on the nearest cluster object. One of the advantages of the k-means method is simple, efficient and easy to apply. In this study, artificial neural network and fuzzy inference system (ANFIS) and Fibonacci Retracement methods are used to predict support and resistance levels. Testing is done using training data and test data with different time intervals. This data produces the highest level of testing based on data from 3 January 2015 - December 2017 and 1 month test data for the period January 2018 100% weekly real data ,. While the value of the accuracy of the trial data period 1 to 2 years and 1 month test data for the period January 2018 daily real data, which is 40%. The average value of the experiment using training data and test data with different time intervals was 52.61%.

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Journal Info

Abbrev

jtim

Publisher

Subject

Computer Science & IT

Description

Cakupan dan ruang lingkup JTIM terdiri dari Databases System, Data Mining/Web Mining, Datawarehouse, Artificial Integelence, Business Integelence, Cloud & Grid Computing, Decision Support System, Human Computer & Interaction, Mobile Computing & Application, E-System, Machine Learning, Deep Learning, ...