Characterization of records in emergencies assisted by INPRADEM using data mining

Yamilet Casanova (), Francisco Hidrobo () and Lucileima Rosales ()
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Yamilet Casanova: Ingeniero de Sistemas de la Universidad de Los Andes. Mérida, Venezuela. Teléfono: (58) 04126630203.
Francisco Hidrobo: Ph.D. En Arquitectura de Computadores de la Universidad Politécnica de Cataluña. Escuela de Ciencias Matemáticas y Computacionales Yachay Tech. Ecuador. Teléfono: (593) 980610529.
Lucileima Rosales: Magister Scientiae en Estadística de la Universidad de Los Andes. Escuela de Estadística. Universidad de Los Andes. Mérida, Venezuela. Teléfono: (58) 04147282629.

Economía, 2019, vol. 44, issue 48, 81-115

Abstract: This article presents the characterization of INPRADEM’s emergency records by using data mining. The methodology used was CRISP-DM, placing an emphasis on: emergencies caused in the Merida State, collisions of hours, weeks with more emergencies and events during vacation periods. The results provide relevant information related to the most used equipment, collision arrangement by hours, emergencies that do or do not require equipment, performance in holiday periods, and days of the week with a greater number of events. INPRADEM has a new way of viewing its data, promising benefits to the solution of a wide range of problems such as: economic planning, work and equipment distribution, service analysis and prevention in periods of high demand.

Keywords: Organization; data mining; characterization (search for similar items in EconPapers)
JEL-codes: C44 C89 D83 (search for similar items in EconPapers)
Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:ula:econom:v:44:y:2019:i:48:p:81-115

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