Optimization of Human Resource Administration System Based on DM Technology and Random Forest Algorithm

Abstract

As the first resource of an enterprise, human resources are the core competitiveness of the enterprise and are paid more and more attention by the enterprise, so that the administration means and technology of human resources are constantly improved, and the human resource administration information system is gradually emerging in the enterprise. As enterprise manpower administration, how to make enterprise administration scientific and rational with the help of data mining(DM) technology, and how to mine information beneficial to enterprise decision-making from a large amount of data, has become an important issue to be considered at present. Based on DM technology and random forest algorithm, this paper studies the human resource administration (HRM) system. There are many different algorithms to realize the unique tree in a random forest. When the number of features reaches 8, the index value of Gini is 0.116, and the index value of Entropy is 0.106. From this, it can be seen that in a random forest, the effect of using the Gini index to manage human resources is better. The random forest can avoid overfitting, and its flexible report generation and analysis functions make human resource managers free from tedious daily work and focus on more challenging and creative human resource analysis, planning, employee motivation, and strategy.