Forecasting Indonesia Stock Exchange (IDX) Composite Using Fuzzy Time Series Methods

Authors : Salang Musikasuwan, Tri Wijayanti Septiarini

Volume/Issue : Volume 5 - 2020, Issue 3 - March

Google Scholar :

Scribd :

The main objective of this research is to propose forecasting model of stock exchange (IDX) composite index using a weighted fuzzy time series (WFTS) model. The Mamdani inference system has been applied with the fuzzy model by using centroid defuzzification. After the models have been executed and verified, the performance of WFTS model has been compared with the conventional fuzzy time series (FTS) model using root mean square error (RMSE). The results showed that WFTS models had better performance than the conventional FTS models. The RMSE values achieved from WFTS and FTS models for training data sets were 0.314 and 0.4443, and for testing data 0.3246 and 0.4351, respectively. Finally, it is recommended that optimization techniques should be employed with the proposed type of models to improve their performance.

Keywords : Forecasting Model; Fuzzy Time Series; Weighted Fuzzy Time Series; Stock Exchange Composite.


Paper Submission Last Date
30 - April - 2024

Paper Review Notification
In 1-2 Days

Paper Publishing
In 2-3 Days

Video Explanation for Published paper

Never miss an update from Papermashup

Get notified about the latest tutorials and downloads.

Subscribe by Email

Get alerts directly into your inbox after each post and stay updated.

Subscribe by RSS

Add our RSS to your feedreader to get regular updates from us.