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| Acadêmico(a): Rafael Semann |
| Título: FERRAMENTA PARA PREDIÇÃO DE DADOS PROEMINENTES DE SISTEMAS RH |
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| Abstract: |
| This work shows the development of a World Wide Web (Web) tool to data mining over a Human Resources (HR), which aims to detect patterns in the turnover of a specific HR. In more detail aim to identify groups that have tendency of been fired or to resign, modify the C4.5 algorithm to allow attributes provides by the text mining, demonstrate a forecasting search on the decision tree, and measure the importance and legitimacy of the generated information to the HR. For the data mining was used the decision tree method over the C4.5 algorithm, in this algorithm was introduced the text mining through an attribute of the same type. Throughout the generated decision tree was used the Predicted Model Markup Language (PMML) to do a search in the dismissal data. Finally demonstrating that the tool is useful to help in the decision-making relative to turnover. |
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