Sales Growth Prediction Using Multiple Linear Regression And K-Nearest Neighbors With Parameters: Asset Structure, Return On Assets, Cash Holding, And Capital Structure

Abstract

ABSTRACT

   Sales growth is one of the important factors in a company, where sales are one of the indices that describe the positive or negative trend of a company towards sales made during the year, this factor can certainly be calculated by correlating several parameters that can affect sales, including asset structure, return on assets, cash holding, and capital structure. In this study, Multiple Linear Regression and K-Nearest Neighbor were used as a tool in predicting the growth of plantation companies listed on the Indonesia Stock Exchange from 2016 to 2020. The results of the study obtained a Mean Absolute Error (MAE) of Multiple Linear Regression of 71.88% and 33.33% for K-Nearest Neighbor so that it can be articulated that the use of K-Nearest Neighbor is more capable of producing more accurate data predictions compared to Multiple Linear Regression.