Modelling Under Uncertainty Business Competitive With Robust Estimation Measurement Model

Abstract

Business insight can be characterized as a bunch of procedures and apparatuses for the obtaining and change of crude information into significant and valuable data for business examination purposes. Information requires strategies and programs that competing organizations in which e-metrics cannot ignore it. Electronic-Metrics or commonly known as e-metrics are data created based on electronic-based customer behavior (e-customer behavior). Extracting information on a competitive organization involves a similarity that is used to find a connection or linkage between organizational behavior. Various new ways are used to achieve success, one of which is with an electronic-based business, but with such a large number of variations, the uncertainty in business is also increasingly difficult to predict. Especially in predicting what activities will often occur in the next few years. Prediction is a process of systematically estimating something that is most likely to happen in the future based on past and present information. 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, whether the value of a company produces the desired results. Optimization can be done with robust nonparametric regression, where robust regression is used to detect outliers and provide results that are resistant to outliers. MM (Method of Moment) estimation is one of the estimates in robust regression that can be used for detected outlier data on the independent and dependent variables. Based on the parameter significance test, it was found that merchants who sell food are more profitable than other merchants. With a difference in iteration value 23.9 and a comparison of iteration value 53.1. Based on the parameter significance test conducted, it was found that merchants who sell food are more.