Determining Next Year’s Iron Price : Application of Linear Regression Algorithm through RapidMiner
Penentuan Harga Besi Tahun Depan : Penerapan Algoritma Regresi Linier melalui RapidMiner
DOI:
https://doi.org/10.21070/ups.4382Keywords:
Business competition, Factors Affecting Price, Linear Regression, Price Prediction, RapidMiner.Abstract
Competition in companies often occurs in the domains of price, advertising and promotion, and quality. There are two objectives in this study, the first objective is to predict the right iron price to be used in the following year so that it can be used to increase the competitiveness of the company. The results of this study are, on training data an accuracy value of 95% was obtained with a threshold value of 30 which stated that the results were accurate. Then the factors that affect the price produce factors from the size variable (mm) and unit (kg), between the two variables that affect the price there are results from the variables that most affect the price, namely size (mm). Produces a value of 199,291 for the performance of the linear regression model calculated using the root mean square error (RMSE).
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