COMPARISON OF STOCK PRICE PREDICTION ACCURACY WITH VARIATION NUMBER OF HIDDEN LAYER CELL IN BACKPROPAGATION ALGORITHM

KRISTIAWAN, DOOHAN (2018) COMPARISON OF STOCK PRICE PREDICTION ACCURACY WITH VARIATION NUMBER OF HIDDEN LAYER CELL IN BACKPROPAGATION ALGORITHM. Other thesis, Unika Soegijapranata Semarang.

[img] Text (COVER)
14.K1.0042 Doohan Kristiawan.COVER.pdf

Download (7MB)
[img] Text (BAB I)
14.K1.0042 Doohan Kristiawan.BAB I.pdf

Download (104kB)
[img] Text (BAB II)
14.K1.0042 Doohan Kristiawan.BAB II.pdf
Restricted to Registered users only

Download (150kB)
[img] Text (BAB III)
14.K1.0042 Doohan Kristiawan.BAB III.pdf

Download (100kB)
[img] Text (BAB IV)
14.K1.0042 Doohan Kristiawan.BAB IV.pdf

Download (233kB)
[img] Text (BAB V)
14.K1.0042 Doohan Kristiawan.BAB V.pdf

Download (908kB)
[img] Text (BAB VI)
14.K1.0042 Doohan Kristiawan.BAB VI.pdf

Download (100kB)
[img] Text (DAFTAR PUSTAKA)
14.K1.0042 Doohan Kristiawan.DAFTAR PUSTAKA.pdf

Download (121kB)
[img] Text (LAMPIRAN)
14.K1.0042 Doohan Kristiawan.LAMPIRAN.pdf

Download (2MB)

Abstract

ABSTRACT Nowadays there are various ways to invest money. The capital market becomes a tantalizing choice for potential investors. The profit from this investment is obtained from the difference between the selling and buying price of the shares. Created program is expected to provide an overview comparison of prediction accuracy from different hidden layer cells amount. Using historical data from yahoo finance to get stock prices in last 12 months. The data is processed using backpropagation algorithm and the process is done by the number of different hidden layer. Eventually the program will give the stock price predictions from four different number of hidden layer. Of all the proceeds will be matched to determine which one has the most precise accuracy. Keyword: Backpropagation, Neural network, Artificial intelligence

Item Type: Thesis (Other)
Subjects: 000 Computer Science, Information and General Works > 004 Data processing & computer science
Divisions: Faculty of Computer Science > Department of Informatics Engineering
Depositing User: Mr Lucius Oentoeng
Date Deposited: 21 Jun 2018 04:26
Last Modified: 21 Jun 2018 04:26
URI: http://repository.unika.ac.id/id/eprint/16182

Actions (login required)

View Item View Item