Data mining for cryptocurrencies price prediction

Abstract

Electronic payments is something that is currently in high demand by investors today, but transactions are often constrained due to various problems, especially from third parties. For this reason, cryptocurrency emerged, which is one of the solutions for conducting electronic payment transactions. Some types of cryptocurrency that are most in demand by investors are bitcoin, ethereum, and ripple. The fluctuation value of cryptocurrency is very difficult to predict so that investors often experience losses when making transactions. This study aims to predict cryptocurrency prices such as bitcoin, ethereum and ripple using data mining algorithms. The data mining algorithm used in this prediction process is K-NN, Neural Network, SVM, Linear Regression, Random Forest and DecisionTree. Data mining modeling is done by dividing the dataset into each type of commodity and then analyzed using each algorithm. The results of this study indicate that the accuracy value obtained from some data mining algorithms is good enough to predict cryptocurrency prices