期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2021
卷号：99
期号：1
页码：114
出版社：Journal of Theoretical and Applied
摘要：Business Intelligence can be used to support various business decisions from operational to strategic. Various new ways have been used to make progress, one of which is with electronic-based businesses, but with a large number of variations, business vulnerabilities are also increasingly difficult to anticipate. To keep up with the development of the company, it is necessary to optimize the metrics for the business. The purpose of optimization is to find the minimum or maximum value of a problem that occurs, whether the value of a company produces the desired results or vice versa. The reason for the improvement is to find a basis or estimate of the difficulty that occurs, regardless of whether the organization's estimate provides an ideal result or vice versa., where the outliers obtained are one of the parameters that can be considered in achieving profit. In this study, the Robust CMARS (Conic Multivariate Adaptive Regression Spline) was used where CMARS can manage the existing multivariate in the data and use a robust approach in handling uncertainty outliers in the data. So that the results achieved by RCMARS are in the form of a maximum value of the basis of the functions BF11, BF12, and BF13 with a maximum of 14.06% outliers.
