Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
October 20, 2025Journal of Computer Science and Technology StudiesOpen Access

Machine Learning Approaches to Salary Prediction in Human Resource Payroll Systems

View Full Paper
Ask AI
Bookmark
Share

Authors

JMJaya Vardhani MamidalaVBVarun BitkuriAAAvinash Attipalli

Discussion

Loading...

Member takes

Overview

Analysis shows that machine learning models improve salary prediction accuracy in HR payroll systems, suggesting significant benefits for workforce management.

Key Points

  • The XGBoost model achieved an AUC-ROC of 0.93, demonstrating high predictive capability.
  • Analysis of the Adult Income Dataset highlighted the advantages of advanced machine learning techniques over traditional methods.
  • Feature selection processes were implemented to enhance the model's efficiency in predicting salaries.
  • The study's findings indicate that using machine learning can lead to more accurate and fair compensation strategies in HR management.

Cite This Study

Mamidala et al. (2025) studied this question.

synapsesocial.com/papers/68f5fcce8d54a28a75cf1ab4https://doi.org/10.32996/jcsts.2025.7.10.52
View Full Paper
Ask AI
Bookmark
Share

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Employee Salary Prediction in HRMS Using Regression Models2024 · 1 citations
  2. 2The investigation and prediction for salary trends in the data science industry2024 · 2 citations
  3. 3Machine Learning in HR Analytics: A Comparative Study on the Predictive Accuracy of Attrition Models2024
  4. 4An AI-Driven Management Information System for Employee Attrition Prediction: Enhancing Human Agency Through XGBoost and Explainable AI2026
  5. 5Skill Demand Forecasting and Salary Prediction: A Multi-Granularity Analysis Using XGBoost2026