Research Article of International Journal of Industrial and Business Management
The Application of Data Mining in Payroll Distribution
Zhong Zheng1*, Lingli Huang2, Tianlong Wang3, Gang Wang4, Wenjie Liu5
1College of Electrical Engineering & New Energy, China Three Gorges University, Yichang, 443002, China. 2College of Science, China Three Gorges University, Yichang, 443002, China. 3College of Civil Engineering & Architecture, China Three Gorges University, Yichang, 443002, China. 4College of Mechanical & Power Engineering, China Three Gorges University, Yichang, 443002, China. 5College of Foreign languages, China Three Gorges University, Yichang, 443002, China
This paper studies the application of data mining in total wage distribution. The wage distribution model based on entropy method and analytic hierarchy process is established. Taking a state-owned enterprise as an example, the data was preprocessed with the linear equation fitting method. Entropy method was used to determine the weight of the influencing factors of wage distribution, and the first 8 factors were selected as the main influencing factors. The analytic hierarchy process (AHP) was used to calculate the weight of contract worker’s salary and contract employees’ salary as 0.342 and 0.658, respectively. On this basis, the total wage distribution. Compare and analyze the established distribution plan with the original distribution plan, and put forward improvement Suggestions to the original distribution plan: should increase the proportion of contract labor.
Keywords: The unitary linear equation fitting; Entropy method; AHP
How to cite this article:
Zhong Zheng, Lingli Huang, Tianlong Wang, Gang Wang, Wenjie Liu. The Application of Data Mining in Payroll Distribution. International Journal of Industrial and Business Management, 2020; 4:17. DOI: 10.28933/ijibm-2020-01-2505
1. Lina Sun, Kai Wang. Comprehensive evaluation and spatial analysis of county economy based on entropy method[J]. Journal of Liaoning university of technology (social science edition), 2019,21(02):21-24.
2. Qi Yu. Overview of data cleaning techniques in data mining[J]. Henan science and technology, 2018(20):21-23.
3. Yu Lu. Based on analytic hierarchy process (AHP), the weight of driving condition is determined[J]. Practical automotive technology, 2019(02):114-117.
4. Zhigang Jian, Xu Jin. Research and realization of data preprocessing in data mining[J]. Re-search in computer applications,2004(07):117-118+157.
5. Wei He, Siyuan Yang. New research on wage reform [J]. China labor science,1990(10):17-20.
This work and its PDF file(s) are licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.