Mahfudhoh, Salis (2015) Peramalan Nilai Transaksi Jual Beli Saham Di Bursa Efek Indonesia Dengan Menggunakan Metode Arimax, Fungsi Transfer, Dan Neural Network. Undergraduate thesis, Institut Teknology Sepuluh Nopember.
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Abstract
Salah satu ukuran keberhasilan BEI dalam mengembangkan
industry pasar modal adalah nilai transaksi jual beli saham setiap
harinya. Ketidakpastian nilai transaksi jual beli saham ini, membuat
BEI bertindak hati-hati dalam mengambil keputusan untuk menentukan
target perusahaan. Oleh karena itu, tujuan penelitian ini dimaksudkan
untuk memprediksi nilai transaksi saham harian serta untuk membantu
BEI menentukan target dan perencanaan strategis perusahaan. Data
yang digunakan dalam penelitian ini mulai periode Januari 2012 hingga
Desember 2015. Metode yang digunakan adalah ARIMAX, fungsi
transfer, dan neural network. Berdasarkan RMSE dan SMAPE
outsample terkecil, model yang sesuai untuk prediksi nilai transaksi
saham harian adalah fungsi transfer. Model ini menjelaskan bahwa
prediktor yang digunakan (IHSG) berkaitan dengan nilai transaksi jual
beli saham harian. Selain itu, terdapat faktor-faktor lain yang
berkaitanyaitu kejadian tak terduga atau shock event (27 Agustus 2012),
kebijakan peraturan baru oleh BEI (25 Maret 2013), kebijakan bursa
luar negeri (18 September 2013) dan kebijakan pemerintah (31 Mei
2013).
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One of success measures for IDX in developing the capital
market is the value of stock trading transactions every day. Due
to uncertainty of stock trading value transactions, it makes IDX
act prudently in making decisions to determine the targets.
Therefore, goals of this research is intended to predict the value
of stock transactions daily, to help IDX in determining targets
and strategic planning. The data used in this study are observed
from January 2012 to December 2015. The methods used are
ARIMAX, transfer functions, and the neural network. Based on
outsample smallest RMSE dan SMAPE, An appropriate model for
the prediction of daily stock transaction value is transfer
function. This model explain that the predictor (JCI) is used in
connection with the value of stock trading transactions. There are
other factors related are influence the unexpected events or shock
event (August 27, 2012), new regulatory policies by the BEI
(March 25, 2013), foreign exchange policy (September 18, 2013),
government policies (May 31, 2013).
| Item Type: | Thesis (Undergraduate) |
|---|---|
| Additional Information: | RSSt 512.943 4 Mah p |
| Uncontrolled Keywords: | ARIMAX, Transfer Function, Neural Network, IDX (Indonesia Stock Exchange) |
| Subjects: | Q Science > QA Mathematics > QA76.87 Neural networks (Computer Science) |
| Divisions: | Faculty of Mathematics and Science > Statistics > 49201-(S1) Undergraduate Thesis |
| Depositing User: | Mr. Tondo Indra Nyata |
| Date Deposited: | 28 Nov 2019 06:58 |
| Last Modified: | 28 Nov 2019 06:58 |
| URI: | http://repository.its.ac.id/id/eprint/72106 |
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