A CLASSIFICATION MODEL WITH FUZZY LOGIC APPROACH IN PREDICTING NETFLIX STOCK PRICE USING EXPONENTIAL REGRESSION

Abstract

Indonesia experienced a significant impact when COVID-19 was declared to be present, especially in the economic aspect. If the Indonesian economy continues to decline without any policies being implemented, it is feared that Indonesia will experience a broad monetary crisis. Based on these problems, Bank Indonesia told the public to invest in the stock market. However, there are some people who are constrained to dare to start investing for fear of experiencing losses, because the future is difficult to predict. In this thesis, a very good forecasting model is obtained by using a fuzzy logic classification approach with exponential regression. Exponential regression is a non-linear regression in which the dependent variable is exponentially distributed, then in the scatter plot a line is formed like an exponential and is a development of linear regression using logarithmic functions. In addition, data classification will be carried out using a fuzzy logic approach. In the data classification stage, criteria parameters with fuzzy membership functions will be used. The author uses stock price data for the Netflix company taken from the Investing.com site from August 5, 2021 to October 24, 2021. The forecast results show very good criteria using a fuzzy logic classification approach model with exponential regression, namely with an AFER value of 3.40%. Keywords : Forecasting, Fuzzy Logic, Exponential Regression.