Gold is a precious metal that is in great demand, because generally the value of gold tends to be stable and the price per gram will increase every year. Gold investment is divided into two, there are digital investments and physical investments. Sometimes in this gold investment investors will experience losses as well as gain profits. To minimize this, a technique is needed to predict the price of gold. Prediction technique is one of the techniques used in Machine Learning. This study aims to predict the price of gold using the Support Vector Regression (SVR) and Linear Regression (LR) algorithms as a comparison. The software that will be used is Jupyter Notebook using the Python programming language. The final result obtained is a graph of the gold price and of the MSE (Mean Squad Error) error on the the SVR Algorithm is 7.524505784357 and LR Algorithm is 4.04444791059
Copyrights © 2022