Pimentel Filho, Max ChiancaOliveira, Fellipe Lucas Filgueira de2024-08-202024-08-202024-08-15OLIVEIRA, Fellipe Lucas Filgueira de. Aplicação de clusterização aglomerativa para identificação de perfis de inadimplência em consumidores de energia elétrica. 2024. 6f. Trabalho de conclusão de curso (Graduação em Engenharia Elétrica) - Departamento de Engenharia Elétrica, Universidade Federal do Rio Grande do Norte, Natal, 2024.https://repositorio.ufrn.br/handle/123456789/59427Machine Learning (ML) techniques have enabled new approaches to corporate management, including the identification of default profiles. This study investigates the implementation of clustering algorithms to segment customers of an electric utility based on their consumption characteristics, payment history and demographic data. The methodology consists of applying agglomerative clustering to segment customers into distinct groups. The results are evaluated in terms of their ability to differentiate default profiles and provide useful information for decision-making. This approach is expected to contribute to the reduction of default rates, as well as to the optimization of the utility's resources}Attribution-NonCommercial-NoDerivs 3.0 Brazilhttp://creativecommons.org/licenses/by-nc-nd/3.0/br/ClusterizaçãoSegmentaçãoInadimplênciaPagamentoEnergia ElétricabachelorThesis