INTEGRATING FUZZY TIME SERIES AND ICHIMOKU KINKO HYO FOR STOCK MARKET FORECASTING AND TRADING SIGNAL IDENTIFICATION: EVIDENCE FROM THE JAKARTA COMPOSITE INDEX

Abstract

The rapid growth of digital investment platforms has increased public participation in stock market investments, creating a need for accurate forecasting and decision-support methods. This study aims to forecast the daily closing prices of the Jakarta Composite Index (JKSE) and provide investment recommendations by integrating the Fuzzy Time Series (FTS) Chen model and the Ichimoku Kinko Hyo indicator. The dataset consists of 1,201 daily JKSE closing price observations collected from Yahoo Finance, covering the period from June 7, 2021, to June 5, 2026. The FTS model was employed to forecast future price movements, while Ichimoku Kinko Hyo was used to identify market trends and trading signals. The results indicate that the FTS model achieved high forecasting accuracy with MAPE, RMSE, and MSE values of 0.0136, 117.79, and 13,875.19, respectively. Furthermore, the Ichimoku analysis revealed a recent shift from a bullish to a bearish trend, suggesting a cautious investment strategy. Overall, the integration of FTS and Ichimoku Kinko Hyo provides an effective framework for stock market forecasting and investment decision-making.