Modelo de caracterización de individuos morosos utilizando algoritmos de Minería de Datos
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Fecha
2021
Autores
Vargas Gálvez, Gerson
Ramírez Villalobos, Frander
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Editor
Universidad Nacional (Costa Rica)
Resumen
Facilita la caracterización de contribuyentes morosos utilizando modelos de aprendizaje supervisado en las municipalidades. Para el desarrollo de este proyecto se realizó una investigación de tipo aplicada, en la misma se busca determinar de una manera efectiva la posibilidad de que los contribuyentes incurran en mora, aplicando técnicas de minería de datos en los registros de información personal de los contribuyentes y su historial de pago de servicios en la Municipalidad. La población de los datos que se utilizaran tiene en consideración los contribuyentes del cantón de Belén el cual contiene un aproximado de 22,000 habitantes de los cuales un número cercano a los 8,000 son clientes activos de la Municipalidad, además se comprenden los registros disponibles en el sistema municipal SIGMB desde el año 2017 al 2021. Por otro lado, se hace uso del padrón electoral el cual contiene la población votante de Costa Rica, también se accede a los archivos maestros de nacimientos, matrimonios y defunciones del país, facilitados por el Tribunal Supremo de Elecciones.
Facilitates the characterization of delinquent taxpayers using supervised learning models in municipalities. For the development of this project, an applied investigation was carried out, in which it seeks to determine in an effective way the possibility that taxpayers incur in arrears, applying data mining techniques in the personal information records of taxpayers and your history of payment of services in the Municipality. The population of the data that will be used takes into account the taxpayers of the canton of Belén, which contains approximately 22,000 inhabitants of which a number close to 8,000 are active clients of the Municipality, in addition to the records available in the system. municipal SIGMB from the year 2017 to 2021. On the other hand, use is made of the electoral register which contains the voting population of Costa Rica, access is also made to the master files of births, marriages and deaths of the country, provided by the Supreme Court of Elections.
Facilitates the characterization of delinquent taxpayers using supervised learning models in municipalities. For the development of this project, an applied investigation was carried out, in which it seeks to determine in an effective way the possibility that taxpayers incur in arrears, applying data mining techniques in the personal information records of taxpayers and your history of payment of services in the Municipality. The population of the data that will be used takes into account the taxpayers of the canton of Belén, which contains approximately 22,000 inhabitants of which a number close to 8,000 are active clients of the Municipality, in addition to the records available in the system. municipal SIGMB from the year 2017 to 2021. On the other hand, use is made of the electoral register which contains the voting population of Costa Rica, access is also made to the master files of births, marriages and deaths of the country, provided by the Supreme Court of Elections.
Descripción
Vargas Gálvez, G. & Ramírez Villalobos, F. (2021). Modelo de caracterización de individuos morosos utilizando algoritmos de Minería de Datos. [Tesis de Licenciatura]. Universidad Nacional, Heredia, Costa Rica.
Palabras clave
ALGORITMOS, ALGORITHMS, MINERIA DE DATOS, DATA MINING, GOBIERNO LOCAL