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Jakarta Stock Exchange (JKSE) forecasting using fuzzy time series

Hansun, Seng (2014) Jakarta Stock Exchange (JKSE) forecasting using fuzzy time series. 2013 International Conference on Robotics, Biomimetics, Intelligent Computational Systems.

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Official URL: https://ieeexplore.ieee.org/document/6743592

Abstract

This paper aims to implement fuzzy time series as a forecasting method in Jakarta Stock Exchange (JKSE) composite index using percentage change as the universe of discourse. Since Chen and Hsu introduced a new method to forecast enrollments in the University of Alabama, a number of methods have been proposed for forecasting the same subject, such as Jilani, Burney, and Ardil, and Stevenson and Porter. In this paper, the approach of Stevenson and Porter is modified and implemented on another subject, i.e. JKSE composite index. The result of this approach in forecasting JKSE composite index, which is an indicator of stock price changes in Indonesia, shows a promising result.

Item Type: Article
Subjects: 000 Computer Science, Information and General Works > 000 Computer Science, Knowledge and Systems > 005 Computer Programming (Algorithm, Programming Language, Applications, Software, Data Security)
000 Computer Science, Information and General Works > 000 Computer Science, Knowledge and Systems > 006 Special Computer Methods (Artificial Intelligence, Machine Learning, 3D Graphics, Digital Video, Data Mining, Augmented Reality)
300 Social Sciences > 330 Economics > 332 Financial Economics (Shares, Investment)
Divisions: Fakultas Teknik Informatika > Program Studi Informatika
Depositing User: mr admin umn
Date Deposited: 19 Oct 2021 08:21
Last Modified: 19 Oct 2021 08:21
URI: http://kc.umn.ac.id/id/eprint/18885

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