Aplicativo android apoyado en business intelligence para medir el nivel de agresividad en los pobladores de Villa Disnarda San Juan Bautista 2021

• Autores: Erda Bazalar, Mehmet Suheyl, Venancino Hoyos, José
• Formato: tesis de grado
• Fecha de Publicación: 2023
• Institución: Universidad Nacional De La Amazonía Peruana
• Repositorio: UNAPIquitos-Institucional
• Lenguaje: español
• OAI Identifier: oai:repositorio.unapiquitos.edu.pe:20.500.12737/9684
• Enlace del recurso: https://hdl.handle.net/20.500.12737/9684
• Nivel de acceso: acceso abierto
• Materia: Aplicaciones para móviles; Agresividad; Ensayo; Tests; Población urbana; https://purl.org/pe-repo/ocde/ford#2.02.04

The objective of this work was to determine to what extent the implementation of an Android application supported by business intelligence manages to measure the level of aggressiveness in the residents of Villa Disnarda in the district of San Juan Bautista 2021. According to the researcher's purpose, it is applied, According to the number of measurements, it is transversal, the sample universe was made up of 50 people who attended the test, the information was collected on an observation sheet, when the residents used and did not use the application, it was applied to all the processes that They involve the dependent variable, that is, effectiveness in the registration of user data, in the registration of the test and in the generation of diagnosis. The results were: in the data recording, using the application, 100% recorded correctly; When they did not use it, 58% correctly recorded their data manually and 42% did not do it correctly. The time in seconds of recording the test, using the application, 100% register the test, placing themselves in the very fast category, by not using the application, 44% register the test and are placed in the delay category, and 56 % records the test and is placed in the too late category. The time to generate a diagnosis, using the application, 100% is located in the very fast category, without using the application, 100% is located in the category that takes too long. In conclusion, the Android application supported by business intelligence is 100% effective in measuring the level of aggressiveness.