Silva Júnior, Antonio Hermes Marques daSouza, Jeremias Silva de2025-07-092025-07-092025-07-04SOUZA, Jeremias Silva de. Análise discriminante linear aplicada aos indicadores de sustentabilidade da Justiça Eleitoral (2023). Orientador: Antônio Hermes Marques da Silva Júnior. 2025. 92 f. Trabalho de Conclusão de Curso (Graduação em Estatística) – Departamento de Estatística, Universidade Federal do Rio Grande do Norte, Natal, 2025.https://repositorio.ufrn.br/handle/123456789/64198The subject of this study is the analysis of sustainability within the scope of the Brazilian Electoral Justice, based on the indicators from the 2023 Sustainability Performance Index, developed and made available by the National Council of Justice. The relevance of this proposal lies in the attempt to understand whether there are patterns in the observed indicators according to the respective sizes of the electoral courts. To investigate this issue, a predictive model was developed using Linear Discriminant Analysis, a supervised machine learning algorithm, with the aim of classifying the courts based on their scores in the presented socio-environmental indicators. The results showed that the socio-environmental indicators have a high capacity to distinguish courts by size, with the vast majority being correctly classified. The discriminant functions highlighted the most relevant coefficients for distinguishing court sizes, and for the misclassified courts, it was possible to identify the structural differences they exhibited in relation to the courts in their actual category. It is concluded that the proposed methodology can complement conventional IDS analyses by offering a different perspective on the relationship between sustainable performance and institutional size.pt-BRAnálise Discriminante LinearAnálise MultivariadaSustentabilidadebachelorThesisCIENCIAS EXATAS E DA TERRA::PROBABILIDADE E ESTATISTICA::ESTATISTICA::ANALISE MULTIVARIADACIENCIAS EXATAS E DA TERRA::PROBABILIDADE E ESTATISTICA::ESTATISTICA::ANALISE DE DADOSCIENCIAS EXATAS E DA TERRA::PROBABILIDADE E ESTATISTICA