Decision Tree Algorithm to Measure Employee Performance Discipline


  • Linda Marlinda STMIK Nusa Mandiri Jakarta
  • Evita Fitri Universitas Nusa Mandiri, Jakarta
  • Siti Nurhasanah Nugraha Universitas Nusa Mandiri, Jakarta
  • Faruq Aziz Universitas Nusa Mandiri, Jakarta
  • Santoso Setiawan Universitas Nusa Mandiri, Jakarta




Data Mining, Decision Tree Algorithm, Employee Performance, Knime


Performance appraisal is done to measure the performance of an employee on the work done. The company conducts performance appraisals on employees at least every six months, involving all employees. This study uses the Absenteeism_at_work dataset. The purpose of this research is to analyze the performance of the Decision Tree algorithm in the classification process. Classification will be grouped into two, namely: disciplined and undisciplined The classification process will be carried out using K-Nime. Algorithm performance measurement using Knime Analytics Platform is open-source software for creating data science models. Knime builds data understanding and designs data science workflows and reusable components using accuracy, recall, and precision parameters. From the research conducted, the results of the Decision Tree algorithm have an accuracy rate of 94.6% while the label No. 5.4%. Based on the nineteen attributes proposed, it can be concluded that the Decision Tree algorithm has better performance.

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Achmad, D. M., & Fauzi, B. S. (2012). Klasifikasi Data Karyawan Untuk Menentukan Jadwal Kerja Menggunakan Metode Decision Tree. Jurnal IPTEK, 16(1), 18–23. Retrieved from .

Jijo, B. T., & Abdulazeez, A. M. (2021). Classification Based on Decision Tree Algorithm for Machine Learning. 02(01), 20–28.

Oliveira, E. L. De, & Fran, R. A. (2019). Absenteeism Prediction in Call Center. 3, 958–968.

Ozdemir, F. (2020). Assessing Employee Attrition Using Classifications Algorithms. 118–122.

Paais, M., & Pattiruhu, J. R. (2020). Effect of Motivation , Leadership , and Organizational Culture on Satisfaction and Employee Performance. 7(8), 577–588.

Raman, M., Kaliappen, N., & Suan, C. L. (2020). A Study on Machine Learning Classifier Models in Analyzing Discipline of Individuals Based on Various Reasons Absenteeism from Work. 361–365.

Sabuhari, R., Sudiro, A., Irawanto, D. W., & Rahayu, M. (2020). The effects of human resource flexibility , employee competency , organizational culture adaptation and job satisfaction on employee performance. 10, 1777–1786.

Sedik, D. (n.d.). Vol4no Data Mining : Evaluating Performance of Employee ’ s using. 4.

Wahid, Z. (2019). Predicting Absenteeism at Work Using Tree-Based Learners.


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How to Cite

Marlinda, L., Fitri , E. ., Nugraha , S. N. ., Aziz, F., & Setiawan , S. . (2022). Decision Tree Algorithm to Measure Employee Performance Discipline. Sinkron : Jurnal Dan Penelitian Teknik Informatika, 7(4), 2223-2230.

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