Banca de QUALIFICAÇÃO: TARYANE CARVALHO PERNE

Uma banca de QUALIFICAÇÃO de MESTRADO foi cadastrada pelo programa.
STUDENT : TARYANE CARVALHO PERNE
DATE: 20/12/2023
TIME: 14:30
LOCAL: LARA - Laboratório de Raciocínio Automatizado
TITLE:

Proposing a model based on machine learning to support employee retention management in the area of laboratory tests

KEY WORDS:

Turnover, Voluntary employee departure, Talent retention, People Analytics

PAGES: 40
BIG AREA: Ciências Exatas e da Terra
AREA: Ciência da Computação
SUBÁREA: Metodologia e Técnicas da Computação
SPECIALTY: Sistemas de Informação
SUMMARY:

The risk management of organizations when dedicated to human capital management becomes the responsibility of the human resources area, in this sense, the efficient retention of talents entails financial impacts and embodies the strategic nature of HR. Turnover is an indicator that helps to evaluate the retention strategies adopted and its relationship, by definition, with the temporal dimension stimulates the motto for the realization of this study. Another factor with repercussions on employee retention is the good image that the company achieves when it is concerned with the level of motivation and journey of its employees, and the use of tools aimed at data analysis emerges as an alternative for efficient retention management. Therefore, consider them sought by this proposal converge to the development of a predictive model which contributes to the evaluation of the temporal dimension linked to the event: leaving work app. And it intends to understand what are the individual characteristics and what are the characteristics organization’s cultural impact on the planned event, with the differential of contemplating pre-employment and postemployment information. For this purpose, analysis of survival due to its methodological supervision with the objective of evaluating the time which it takes until the movement of interest has changed, adding aspects of interest of the business, such as whether the exit was intentional or involuntary. The results observed so far point to the existence of non-proportionality between the probability distributions related to the characteristics to be used in the model, and reinforces the importance of retention management with a view and control of probabilities of turnover occurring.

COMMITTEE MEMBERS:
Presidente - 402520 - MARCELO LADEIRA
Interno - 2866456 - GLADSTON LUIZ DA SILVA
Interno - 2518570 - MARCOS FAGUNDES CAETANO
Externa ao Programa - 1764333 - ELAINE RABELO NEIVA - UnB