PERAMALAN HARGA SAHAM DENGAN MENGGUNAKAN JARINGAN SYARAF TIRUAN METODE EXTREME LEARNING MACHINE
Abstract: Stock prices
forecasting is one of the way to reduce risk of stock ownership by making price
prediction next day based on previous day. The purpose of this undergraduate
paper is to get stock prediction technically from several companies using
Artificial Neural Network with Extreme Learning Machine method. Extreme
Learning Machine (ELM) is a new learning method in Artificial Neural etwork (ANN)
model with single-layer feedforward neural networks (SLFNs). In predicting
stock prices, data will be trained and look the most optimum weight. Then,
using testing data training process, data will test how good the patterns are
recognized by the network until minimal error obtained. With the validation test,
data will be obtained the value of forecasting stock prices the next day using
optimal weights of the training process.
Keywords: Extreme Learning Machine, Artificial Neural Network, Single Layer Feedforward Neural Networks,
Testing Data Training, Validation Test
Penulis: Muhammad Safiq Ubay,
Auli Damayanti, Herry Suprajitno
Kode Jurnal: jpmatematikadd130071
