Measles is a highly infectious disease caused by Morbillivirus genus and the Paramyxoviridae family. This disease continues to pose a major public health concern despite decades of vaccination efforts because it can cause death. The virus carries a non-segmented, negative-sense RNA genome and spreads solely among humans, primarily through respiratory droplets, with secondary attack rates in susceptible close contacts often exceeding 90%. The disease remains widespread throughout the world, with the highest impact in Africa and Southeast Asia, and causes around 100,000 deaths annually. Although vaccination has prevented millions of deaths, measles-related fatalities persist, highlighting the need for improved elimination strategies. This study applies a bioinformatics approach by using Principal Component Analysis or PCA to create a solution called GeneArcana to investigate genetic variations and analyze measles from a geographic and genomic viewpoint. The result shows Single Nucleotide Polymorphisms or SNPs have similar patterns of susceptibility to measles across diverse ethnicities. Authors hope the solution can provide useful information to design more effective vaccine implementations.