Open AccessPREDICTING THE BITCOIN PRICE USING LINEAR REGRESSION OPTIMIZED WITH EXPONENTIAL SMOOTHING
Author(s) -
Ida Suryani,
Hani Harafani
Publication year - 2021
Publication title -
jurnal riset informatika
Language(s) - English
Resource type - Journals
eISSN - 2656-1743
pISSN - 2656-1735
DOI - 10.34288/jri.v3i3.238
Subject(s) - exponential smoothing , linear regression , exponential function , smoothing , econometrics , regression , series (stratigraphy) , time series , regression analysis , mathematics , statistics , computer science , paleontology , mathematical analysis , biology
Bitcoin is one of the most popular cryptocurrencies today. In the current pandemic conditions that hit the world due to Covid-19, bitcoin is expected to be used as an investment when the level of economic uncertainty is high. In this study, the data used is bitcoin price data which is included in time series data. One of the commonly used methods for prediction in time series is the linear regression method. And to be able to develop the prediction results, a data transformation technique is used using the popular method, namely exponential smoothing. In the exponential smoothing method, optimization of the alpha parameter is carried out to be able to boost the prediction results from linear regression. And from the experimental results, it is evident that the optimization of the alpha parameter in exponential smoothing is able to improve the prediction performance of linear regression with the results of the comparison of RMSE with the t test which has resulted in significant differences.