Web system to enhance technical supervision of incidents at the hydrocarbons regulatory institution in Lima–2023

Descripción del Articulo

In this article, the implementation of a web system was carried out to improve the process of technical supervision of incidents of a hydrocarbon regulatory company because time was lost in carrying out each process; this research was developed using the SCRUM methodology as it is an agile methodolo...

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Detalles Bibliográficos
Autores: Caceres Sanchez, Cynthia Elvia, Diburga Evangelista, Luis Alfredo, Cano Lengua, Miguel Angel, Rosas Culcos, Fredy Robert
Formato: artículo
Fecha de Publicación:2025
Institución:Universidad Tecnológica del Perú
Repositorio:UTP-Institucional
Lenguaje:inglés
OAI Identifier:oai:repositorio.utp.edu.pe:20.500.12867/14636
Enlace del recurso:https://hdl.handle.net/20.500.12867/14636
https://doi.org/10.11591/eei.v14i1.7701
Nivel de acceso:acceso abierto
Materia:Hydrocarbons
Incidents
System
Process
https://purl.org/pe-repo/ocde/ford#5.02.04
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dc.title.es_PE.fl_str_mv Web system to enhance technical supervision of incidents at the hydrocarbons regulatory institution in Lima–2023
title Web system to enhance technical supervision of incidents at the hydrocarbons regulatory institution in Lima–2023
spellingShingle Web system to enhance technical supervision of incidents at the hydrocarbons regulatory institution in Lima–2023
Caceres Sanchez, Cynthia Elvia
Hydrocarbons
Incidents
System
Process
https://purl.org/pe-repo/ocde/ford#5.02.04
title_short Web system to enhance technical supervision of incidents at the hydrocarbons regulatory institution in Lima–2023
title_full Web system to enhance technical supervision of incidents at the hydrocarbons regulatory institution in Lima–2023
title_fullStr Web system to enhance technical supervision of incidents at the hydrocarbons regulatory institution in Lima–2023
title_full_unstemmed Web system to enhance technical supervision of incidents at the hydrocarbons regulatory institution in Lima–2023
title_sort Web system to enhance technical supervision of incidents at the hydrocarbons regulatory institution in Lima–2023
author Caceres Sanchez, Cynthia Elvia
author_facet Caceres Sanchez, Cynthia Elvia
Diburga Evangelista, Luis Alfredo
Cano Lengua, Miguel Angel
Rosas Culcos, Fredy Robert
author_role author
author2 Diburga Evangelista, Luis Alfredo
Cano Lengua, Miguel Angel
Rosas Culcos, Fredy Robert
author2_role author
author
author
dc.contributor.author.fl_str_mv Caceres Sanchez, Cynthia Elvia
Diburga Evangelista, Luis Alfredo
Cano Lengua, Miguel Angel
Rosas Culcos, Fredy Robert
dc.subject.es_PE.fl_str_mv Hydrocarbons
Incidents
System
Process
topic Hydrocarbons
Incidents
System
Process
https://purl.org/pe-repo/ocde/ford#5.02.04
dc.subject.ocde.es_PE.fl_str_mv https://purl.org/pe-repo/ocde/ford#5.02.04
description In this article, the implementation of a web system was carried out to improve the process of technical supervision of incidents of a hydrocarbon regulatory company because time was lost in carrying out each process; this research was developed using the SCRUM methodology as it is an agile methodology and adapted to our research. Using the process, events and artifact, it was possible to design the prototypes of the system, architecture, and database. Finally, the implementation was carried out among other important points obtained as results; the average level of optimization of the incident assignment process, derived from the observations, is 91.05% efficiency in assigning incidents to specialists. Regarding the 95% confidence interval for this indicator, it is between 88.98% and 93.11% efficiency, representing two standard deviations with respect to the mean. Regarding the average response time to incidents in all states, obtained from observations, it is 15 days. The 95% confidence interval for this indicator ranges between 14 and 18 days, which represents two standard deviations from the mean. The system is intuitive and not complex. With the implementation of the web system, processes are automated and end user satisfaction is obtained.
publishDate 2025
dc.date.accessioned.none.fl_str_mv 2025-11-13T18:44:47Z
dc.date.available.none.fl_str_mv 2025-11-13T18:44:47Z
dc.date.issued.fl_str_mv 2025
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dc.identifier.uri.none.fl_str_mv https://hdl.handle.net/20.500.12867/14636
dc.identifier.journal.es_PE.fl_str_mv Bulletin of Electrical Engineering and Informatics
dc.identifier.doi.none.fl_str_mv https://doi.org/10.11591/eei.v14i1.7701
identifier_str_mv 2302-9285
Bulletin of Electrical Engineering and Informatics
url https://hdl.handle.net/20.500.12867/14636
https://doi.org/10.11591/eei.v14i1.7701
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language eng
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dc.publisher.es_PE.fl_str_mv Institute of Advanced Engineering and Science
dc.source.es_PE.fl_str_mv Repositorio Institucional - UTP
Universidad Tecnológica del Perú
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spelling Caceres Sanchez, Cynthia ElviaDiburga Evangelista, Luis AlfredoCano Lengua, Miguel AngelRosas Culcos, Fredy Robert2025-11-13T18:44:47Z2025-11-13T18:44:47Z20252302-9285https://hdl.handle.net/20.500.12867/14636Bulletin of Electrical Engineering and Informaticshttps://doi.org/10.11591/eei.v14i1.7701In this article, the implementation of a web system was carried out to improve the process of technical supervision of incidents of a hydrocarbon regulatory company because time was lost in carrying out each process; this research was developed using the SCRUM methodology as it is an agile methodology and adapted to our research. Using the process, events and artifact, it was possible to design the prototypes of the system, architecture, and database. Finally, the implementation was carried out among other important points obtained as results; the average level of optimization of the incident assignment process, derived from the observations, is 91.05% efficiency in assigning incidents to specialists. Regarding the 95% confidence interval for this indicator, it is between 88.98% and 93.11% efficiency, representing two standard deviations with respect to the mean. Regarding the average response time to incidents in all states, obtained from observations, it is 15 days. The 95% confidence interval for this indicator ranges between 14 and 18 days, which represents two standard deviations from the mean. The system is intuitive and not complex. 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