Performance Analysis of Multiple Linear Regression and Random Forest for an Estimate of the Price of a House

The house is a human need for boards. House prices that continue to rise every year make it difficult for some people to buy a house according to their respective financial capabilities. Many property developers in big cities continue to build housing, including the South Jakarta area with many new arrivals. In this study, we will predict house prices using a comparison of 2 methods, multiple linear regression and random forest which produces a better RMSE value at an 8:2 comparison between training data and testing data, and the multiple linear regression method produces fewer errors. The 8:2 experiment produces an RMSE 3673441811.575 of Linear Regression and 3693111743.726 of Random Forest.