APPLICATION OF FUZZY TIME SERIES WITH FIBONACCI RETRACEMENT FOR FORECASTING STOCK PRICE PT. BANK RAKYAT INDONESIA

Abstract

Stock can be defined as securities that indicate the ownership of a person or legal entity to the company issuing the shares. Good stocks for long-term investment are stocks that have good fundamentals and large market capitalization. The purpose of investing is to make a profit. In investing in stocks, investors need to know the risk management that can affect the ups and downs of a stock. Forecasting or forecasting is an analysis to predict everything related to the production, supply, demand, and use of technology in an industry or business. One of the forecasting methods is using fuzzy time series. The primary purpose of fuzzy time series is to predict time series data that can widely use on any real-time data, including capital market data. In this study, we will discuss the evolution of the time series model in overcoming fluctuations that often occur in stock prices by using a fuzzy time series that combines a stock analysis approach, namely Fibonacci retracement. The stock data used in this study is the close price of BBRI for October 2021 to March 2022. Forecasting results for 1 April 2022 are IDR 4660.49 with a Mean Absolute Percentage forecasting accuracy value of 1.034%.