Jakarta Stock Exchange (JKSE) forecasting using fuzzy time series

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.