Modelling Under Uncertainty Business Competitive With Robust Estimation Measurement Model

Marischa Elveny Et.Al

doi:10.17762/turcomat.v12i3.1820

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.

Highlights

Business Intelligence and Analytics (BIA) is an assortment of techniques, measures, designs, applications and innovations that gather and change crude information into significant and valuable data used to empower more compelling methodologies, strategic experiences, and tasks in dynamic [1]
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

Summary

Introduction

Business Intelligence and Analytics (BIA) is an assortment of techniques, measures, designs, applications and innovations that gather and change crude information into significant and valuable data used to empower more compelling methodologies, strategic experiences, and tasks in dynamic [1]. The approach is carried out by analyzing customer profiles based on the level of behavior similarity, Basic measurements of ModellingUnder Uncertainty Business Competitive With Robust Estimation Measurement Model distances, attributes, times, places, and transactions between social actors are used to trace the origin of the information, or can be used to predict social behaviour [7]. Based on the research that has been done before, this research was conducted to can produce an optimization model in predicting profits with e-metrics data that has not been done by previous research, based on customer profiles by approaching robust nonparametric regression. From the e-metric, the data is grouped based on location, the same merchant type, and different merchant types This is intended to see customer behavior when transacting at a merchant that results in competition from each merchant. Customer purchases can be represented by several variables which can be seen in table 2 below:

Result and Discussion

Iteration Results

Conclusion