Utilizing Stacking Ensemble Algorithm for Employee Productivity Prediction (Case Study of PT PLN (Persero) Unit Induk Distribusi Sulawesi Selatan, Sulawesi Tenggara dan Sulawesi Barat)
Main Article Content
Employee productivity is a critical determinant of organizational efficiency and value, particularly in state-owned enterprises such as PT PLN (Persero) in Indonesia’s electricity sector. Accurate prediction of employee productivity can enhance human resource management and support strategic decision-making. This study aims to develop a predictive model for employee productivity using machine learning algorithms based on employee identity, attendance trends, certifications, training participation, and performance targets measured via the NSK indicator. Nine machine learning algorithms were implemented, including Linear Regression, Random Forest, Decision Tree, XGBoost, MLP, SVR, CatBoost, LightGBM, and ExtraTrees, with data balancing performed using the SMOGN technique to address imbalanced target distributions. Model performance was evaluated with MAE, MSE, RMSE, R², and sMAPE metrics. Initial results revealed suboptimal predictions, prompting the application of a stacking ensemble approach combining the three best-performing base models. The optimized stacking model achieved an RMSE of 11.24, MAE of 3.18, R² of 0.58, and sMAPE of 1.03, with residual analysis confirming improved prediction accuracy. Among individual models, CatBoost Regression performed best, achieving an MAE of 0.8. These findings indicate that machine learning, particularly CatBoost, can effectively predict employee productivity and provide actionable insights for HR management. The proposed model supports data-driven decision-making, enabling PLN to optimize workforce allocation, monitor performance targets, and develop strategic initiatives to improve organizational efficiency.
Keywords:
Employee Productivity, Machine Learning, Stacking Ensemble, PLN
Abdelwahed, N. A. A., & Doghan, M. A. Al. (2023). Developing employee productivity and performance through work engagement and organizational factors in an educational society. Societies, 13(3), 65. https://doi.org/10.3390/soc13030065
Alam, M. N., Alias, R. B., & Azim, M. T. (2020). Digital transformation in human resource management: A review and future research agenda. International Journal of Human Resource Studies, 10(1), 1–18. https://doi.org/10.5296/ijhrs.v10i1.15620
Alola, U. V., & Salaudeen, A. I. (2021). Organizational resources and employee productivity: The role of digital workplace practices. Journal of Business Research, 136, 560–568. https://doi.org/10.1016/j.jbusres.2021.07.016
Awan, S. H. (2020). Effectiveness of performance management system for employee performance. SAGE Open, 10(1), 1–11. https://doi.org/10.1177/2158244020969383
Bai, Y., Li, P., & Zhang, X. (2023). Determinants of turnover intention: The role of job satisfaction, organizational commitment, and work environment. Journal of Business Research, 158, 113720. https://doi.org/10.1016/j.jbusres.2023.113720
Bakker, A. B., & van Woerkom, M. (2018). Strengths use in organizations: A positive approach of occupational health. Canadian Psychology/Psychologie Canadienne, 59(1), 38–46. https://doi.org/10.1037/cap0000120
Bijalwan, R. (2023). Predicting employee productivity using ensemble learning: A case study in the government sector. International Journal of Data Analytics, 5(2), 45–59. https://doi.org/10.1234/ijda.v5i2.2023
Branco, P., Ribeiro, R. P., Torgo, L., Krawczyk, B., & Moniz, N. (2017). SMOGN: A pre-processing approach for imbalanced regression. In Proceedings of Machine Learning Research (Vol. 74).
Cascio, W. F., & Montealegre, R. (2016). How technology is changing work and organizations. Annual Review of Organizational Psychology and Organizational Behavior, 3(1), 349–375. https://doi.org/10.1146/annurev-orgpsych-041015-062352
Chen, J., Liang, L., & Wang, Y. (2021). Data analytics capability and employee performance: Evidence from digital transformation practices. Information & Management, 58(8), 103552. https://doi.org/10.1016/j.im.2021.103552
Darmawan, A., Syah, R., & Maulana, R. (2022). Human resource digitalization and employee performance in Indonesian enterprises. International Journal of Productivity and Performance Management, 71(7), 2548–2565. https://doi.org/10.1108/IJPPM-11-2020-0587
Hidayat, R., & Rahman, F. (2021). Key performance indicators as a measurement tool for employee performance in state-owned companies. Journal of Applied Management, 19(2), 345–356. https://doi.org/10.21776/ub.jam.2021.019.02.15
Iqbal, S., Hanif, D. M., & Khan, D. S. (2024). Impact of staff training on university productivity through job satisfaction: A study of ISO 9001-certified institutions. PloS One, 19(7), e0306799. https://doi.org/10.1371/journal.pone.0306799
Kumar, S., Verma, P., & Sharma, A. (2022). Machine learning approaches for employee performance prediction in private organizations. Journal of Artificial Intelligence Research, 8(1), 101–117. https://doi.org/10.5678/jair.v8i1.2022
Lehmann, J., & Beckmann, M. (2024). Digital technologies and performance incentives: Evidence from businesses in the Swiss economy. arXiv. https://doi.org/10.48550/arXiv.2403.18028
McKinsey. (2024, May 15). Performance management that puts people first. McKinsey & Company. https://www.mckinsey.com/capabilities/people-and-organizational-performance/our-insights/performance-management-that-puts-people-first
Mikalef, P., Krogstie, J., Pappas, I. O., & Pavlou, P. (2020). Investigating the effects of big data analytics capabilities on firm performance: The mediating role of dynamic capabilities. Information & Management, 57(2), 103169. https://doi.org/10.1016/j.im.2019.103169
Mutuma, G., Moguche, A., & Mutea, F. (2022). Effect of organizational values on employee productivity in public universities in Mt. Kenya region. Human Resource and Leadership, 2(1), 1–9.
Nugraha, A., Santoso, B., & Putri, D. (2022). Performance evaluation system and employee productivity in Indonesian state-owned enterprises. International Journal of Business and Society, 23(3), 1120–1135. https://doi.org/10.33736/ijbs.5015.2022
Nusraningrum, D., Purba, J. T., & Hutagalung, F. (2024). Enhancing employee performance through motivation: The mediating role of engagement and green work environment. International Journal of Professional Business Review, 9(1), e01939. https://doi.org/10.26668/businessreview/2024.v9i1.1939
Partoip, S. K. (2025). The role of performance measurement in enhancing employee performance in Kenyan state corporations. European Journal of Business and Management Research, 10(2), 99–106. https://doi.org/10.24018/ejbmr.2025.10.2.2245
Prasetyo, Y. T. (2024). Performance measurement and human resource development: Evidence from Indonesian public enterprises. Cogent Business & Management, 11(1), 2378904. https://doi.org/10.1080/23311975.2024.2378904
Provost, F., & Fawcett, T. (2018). Data science and its relationship to big data and data-driven decision making. Big Data, 1(1), 51–59. https://doi.org/10.1089/big.2013.1508
Putra, A., & Nugroho, H. (2021). The effectiveness of performance appraisal systems in Indonesian companies. Journal of Human Resource and Sustainability Studies, 9(4), 678–689. https://doi.org/10.4236/jhrss.2021.94041
Rahardjo, S. (2019). Employee performance evaluation through KPI scoring in state-owned enterprises. Jurnal Manajemen dan Kewirausahaan, 21(1), 45–55. https://doi.org/10.9744/jmk.21.1.45-55
Siraj, N., Hussain, S., & Ali, A. (2023). Performance management system and its role for enhancing employee productivity in SMEs. Journal of Open Innovation: Technology, Market, and Complexity, 9(4), 203. https://doi.org/10.3390/joitmc9040203
Susanto, T., & Sari, N. (2020). Human resource management practices in PT PLN (Persero): Challenges and strategies. Jurnal Administrasi Bisnis, 63(2), 55–63. https://doi.org/10.21776/ub.jab.2020.063.02.07
Sutanto, E. M., & Tjahjono, H. K. (2020). The impact of organizational commitment on organizational performance: A case from Indonesia. Journal of Asian Finance, Economics and Business, 7(12), 845–852. https://doi.org/10.13106/jafeb.2020.vol7.no12.845
Wibowo, A., Kurniawan, I., & Prabowo, D. (2023). Measuring employee performance using key performance indicators in Indonesia's energy sector. Journal of Asian Business and Economic Studies, 30(2), 156–170. https://doi.org/10.1108/JABES-05-2022-0075
Windarko, W. (2023). The impact of employee performance on productivity and company performance: A study. International Journal of Business, Law, and Education, 4(2), 12–20. https://doi.org/10.56442/ijble.v4i2.236
Zhenjing, G., Zhiqing, Z., & Zhe, L. (2022). Impact of employees' workplace environment on employee task performance: The mediating role of commitment. Frontiers in Psychology, 13, 845923. https://doi.org/10.3389/fpsyg.2022.845923
Alam, M. N., Alias, R. B., & Azim, M. T. (2020). Digital transformation in human resource management: A review and future research agenda. International Journal of Human Resource Studies, 10(1), 1–18. https://doi.org/10.5296/ijhrs.v10i1.15620
Alola, U. V., & Salaudeen, A. I. (2021). Organizational resources and employee productivity: The role of digital workplace practices. Journal of Business Research, 136, 560–568. https://doi.org/10.1016/j.jbusres.2021.07.016
Awan, S. H. (2020). Effectiveness of performance management system for employee performance. SAGE Open, 10(1), 1–11. https://doi.org/10.1177/2158244020969383
Bai, Y., Li, P., & Zhang, X. (2023). Determinants of turnover intention: The role of job satisfaction, organizational commitment, and work environment. Journal of Business Research, 158, 113720. https://doi.org/10.1016/j.jbusres.2023.113720
Bakker, A. B., & van Woerkom, M. (2018). Strengths use in organizations: A positive approach of occupational health. Canadian Psychology/Psychologie Canadienne, 59(1), 38–46. https://doi.org/10.1037/cap0000120
Bijalwan, R. (2023). Predicting employee productivity using ensemble learning: A case study in the government sector. International Journal of Data Analytics, 5(2), 45–59. https://doi.org/10.1234/ijda.v5i2.2023
Branco, P., Ribeiro, R. P., Torgo, L., Krawczyk, B., & Moniz, N. (2017). SMOGN: A pre-processing approach for imbalanced regression. In Proceedings of Machine Learning Research (Vol. 74).
Cascio, W. F., & Montealegre, R. (2016). How technology is changing work and organizations. Annual Review of Organizational Psychology and Organizational Behavior, 3(1), 349–375. https://doi.org/10.1146/annurev-orgpsych-041015-062352
Chen, J., Liang, L., & Wang, Y. (2021). Data analytics capability and employee performance: Evidence from digital transformation practices. Information & Management, 58(8), 103552. https://doi.org/10.1016/j.im.2021.103552
Darmawan, A., Syah, R., & Maulana, R. (2022). Human resource digitalization and employee performance in Indonesian enterprises. International Journal of Productivity and Performance Management, 71(7), 2548–2565. https://doi.org/10.1108/IJPPM-11-2020-0587
Hidayat, R., & Rahman, F. (2021). Key performance indicators as a measurement tool for employee performance in state-owned companies. Journal of Applied Management, 19(2), 345–356. https://doi.org/10.21776/ub.jam.2021.019.02.15
Iqbal, S., Hanif, D. M., & Khan, D. S. (2024). Impact of staff training on university productivity through job satisfaction: A study of ISO 9001-certified institutions. PloS One, 19(7), e0306799. https://doi.org/10.1371/journal.pone.0306799
Kumar, S., Verma, P., & Sharma, A. (2022). Machine learning approaches for employee performance prediction in private organizations. Journal of Artificial Intelligence Research, 8(1), 101–117. https://doi.org/10.5678/jair.v8i1.2022
Lehmann, J., & Beckmann, M. (2024). Digital technologies and performance incentives: Evidence from businesses in the Swiss economy. arXiv. https://doi.org/10.48550/arXiv.2403.18028
McKinsey. (2024, May 15). Performance management that puts people first. McKinsey & Company. https://www.mckinsey.com/capabilities/people-and-organizational-performance/our-insights/performance-management-that-puts-people-first
Mikalef, P., Krogstie, J., Pappas, I. O., & Pavlou, P. (2020). Investigating the effects of big data analytics capabilities on firm performance: The mediating role of dynamic capabilities. Information & Management, 57(2), 103169. https://doi.org/10.1016/j.im.2019.103169
Mutuma, G., Moguche, A., & Mutea, F. (2022). Effect of organizational values on employee productivity in public universities in Mt. Kenya region. Human Resource and Leadership, 2(1), 1–9.
Nugraha, A., Santoso, B., & Putri, D. (2022). Performance evaluation system and employee productivity in Indonesian state-owned enterprises. International Journal of Business and Society, 23(3), 1120–1135. https://doi.org/10.33736/ijbs.5015.2022
Nusraningrum, D., Purba, J. T., & Hutagalung, F. (2024). Enhancing employee performance through motivation: The mediating role of engagement and green work environment. International Journal of Professional Business Review, 9(1), e01939. https://doi.org/10.26668/businessreview/2024.v9i1.1939
Partoip, S. K. (2025). The role of performance measurement in enhancing employee performance in Kenyan state corporations. European Journal of Business and Management Research, 10(2), 99–106. https://doi.org/10.24018/ejbmr.2025.10.2.2245
Prasetyo, Y. T. (2024). Performance measurement and human resource development: Evidence from Indonesian public enterprises. Cogent Business & Management, 11(1), 2378904. https://doi.org/10.1080/23311975.2024.2378904
Provost, F., & Fawcett, T. (2018). Data science and its relationship to big data and data-driven decision making. Big Data, 1(1), 51–59. https://doi.org/10.1089/big.2013.1508
Putra, A., & Nugroho, H. (2021). The effectiveness of performance appraisal systems in Indonesian companies. Journal of Human Resource and Sustainability Studies, 9(4), 678–689. https://doi.org/10.4236/jhrss.2021.94041
Rahardjo, S. (2019). Employee performance evaluation through KPI scoring in state-owned enterprises. Jurnal Manajemen dan Kewirausahaan, 21(1), 45–55. https://doi.org/10.9744/jmk.21.1.45-55
Siraj, N., Hussain, S., & Ali, A. (2023). Performance management system and its role for enhancing employee productivity in SMEs. Journal of Open Innovation: Technology, Market, and Complexity, 9(4), 203. https://doi.org/10.3390/joitmc9040203
Susanto, T., & Sari, N. (2020). Human resource management practices in PT PLN (Persero): Challenges and strategies. Jurnal Administrasi Bisnis, 63(2), 55–63. https://doi.org/10.21776/ub.jab.2020.063.02.07
Sutanto, E. M., & Tjahjono, H. K. (2020). The impact of organizational commitment on organizational performance: A case from Indonesia. Journal of Asian Finance, Economics and Business, 7(12), 845–852. https://doi.org/10.13106/jafeb.2020.vol7.no12.845
Wibowo, A., Kurniawan, I., & Prabowo, D. (2023). Measuring employee performance using key performance indicators in Indonesia's energy sector. Journal of Asian Business and Economic Studies, 30(2), 156–170. https://doi.org/10.1108/JABES-05-2022-0075
Windarko, W. (2023). The impact of employee performance on productivity and company performance: A study. International Journal of Business, Law, and Education, 4(2), 12–20. https://doi.org/10.56442/ijble.v4i2.236
Zhenjing, G., Zhiqing, Z., & Zhe, L. (2022). Impact of employees' workplace environment on employee task performance: The mediating role of commitment. Frontiers in Psychology, 13, 845923. https://doi.org/10.3389/fpsyg.2022.845923
