Evaluation of Active Affiliates to the SIS Multidimensional Analysis in R Shiny

This article presents a study that uses multiple linear regression analysis to examine the factors influencing the number of people affiliated with different insurance plans within the Comprehensive Health Insurance (SIS) system in Peru.The study highlights the importance of multiple linear regression analysis in understanding the factors that affect SIS Comprehensive Health Insurance affiliates. It also showcases the value of utilizing interactive tools like RShiny to enhance data analysis, providing a dynamic and participatory experience for researchers and users interested in the subject.To facilitate the analysis and visualization of SIS-related data, the researchers developed an interactive application using RShiny. This tool allows for the easy loading, visualization, and analysis of data in a user-friendly and practical manner. By providing an interactive platform, users can effectively explore and understand the factors that impact SIS affiliates.The results of the analysis indicate that the selected variables have a significant positive influence on the total number of affiliates. This suggests that the specific insurance plan examined in this study has a favorable effect on the enrollment of individuals in SIS. Additionally, the data shows a linear trend, supporting the use of a linear regression model to describe this relationship. Active affiliates,Comprehensive health insurance SIS,Data Visualization,Multiple Linear Regression Analysis,RShiny