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@article{191855,
        author = {K. MANJU and S. SHIRELY},
        title = {SALARY PREDICTION SYSTEM USING MACHINE LEARNING},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {8},
        pages = {8066-8069},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=191855},
        abstract = {The rapid growth of digital payment systems has increased the volume of financial transactions, making salary processing and payroll management more complex. Traditional payroll systems mainly focus on payment execution and lack intelligent analytical capabilities. This project proposes a Smart Pay Analytics system that uses Machine Learning techniques to analyze payroll dataset detect salary anomalies, identify unusual payment patterns, and generate meaningful insights for organizations. By applying data preprocessing, feature extraction, and classification models, the system helps organizations improve financial transparency, reduce payroll fraud, and support better decision-making. The proposed system ensures accuracy, security, and efficiency in payroll analytics.},
        keywords = {Salary Prediction, Machine Learning, Data Preprocessing, Random Forest, TF-IDF, Predictive Analytics, Web Application, Automation, Python Flask.},
        month = {January},
        }