Modeling coal company stock by using fuzzy-RBFNN

Brodjol Sutijo Suprih Ulama, Mike Prastuti, Apratnya Paramitha Oktaviana

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

In the last three years the Indonesian Composite Stock Price Index (CSPI) experienced significant growth, 17.02%. Indonesia stock exchange especially mining sector increase rapidly. In 2018, mining sector stock index is second highest growth after consumption sector, from 1,593.99 in 2017 become 1,991.61 in february 2018. The growthof price mining stock was triggered by rising commodity price, so financial performanc of mining corporate also increase. Based on the above description, it is necessary to know how long mining sector shares will continue to rise, thus helping investors to do adjustment on investment. There are many methods to forecast such as ARIMA, Aritficial Neural Network, and Fuzzy Neural Network (FNN). FNN especially Fuzzy Radial Basis Fuction Neural Network (Fuzzy-RBFNN) is going to use to modelling stock price of three mining company sector. Based on models, generally seven cluster of input model give more accurate than less.

Original languageEnglish
Pages (from-to)858-865
Number of pages8
JournalInternational Journal of Mechanical Engineering and Technology
Volume9
Issue number858-865
Publication statusPublished - 1 Dec 2018

Keywords

  • ARIMA
  • Fuzzy Neural Network
  • Fuzzy-RBFNN
  • Stock

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