Employee Performance Assessment Model in Survey Service Companies Using Analytical Hierarchy Process and Naive Bayes

Heni  Hindayanti; Winnie Septiani; Rahmi  Maulidya

doi:10.12928/si.v22i1.150

Authors

Heni Hindayanti Universitas Trisakti
Winnie Septiani Universitas Trisakti
Rahmi Maulidya Universitas Trisakti

DOI:

https://doi.org/10.12928/si.v22i1.150

Keywords:

Assessment, Employee Performance, Analytical Hierarchy Process, Naïve Bayes, 360 Degree Feedback

Abstract

Assessment of the performance of employees of a survey service company produces a final score that is not in accordance with the company's transformation strategy in responding to external challenges and demands. The variable assessment process still uses 180 Degree Feedback which is one-way from superiors to employees. This makes the company's learning and growth activities, especially in the human resources department, not occur. Therefore, companies should improve the assessment model to become a tool for acquiring highly qualified performing employees. This study contributes to obtain a more comprehensive employee performance assessment model proposal and evaluate the model so that it can be implemented. The research limitation lies in the use of data, namely contract employees with the position of Project Manager. This study uses the Analytical Hierarchy Process and Naïve Bayes methods to obtain variable weights. Based on the results of the analysis, it was found that SOE (State Owned Enterprises) AKHLAK was a new variable. The classification of the assessment variables is divided into Performance and Behavioral aspects based on the Minister of SOE Regulation. Changes that occur include formulas, mechanisms, and rating scales. The results of the verification and validation show that the model is in accordance with the design so that it can be implemented. Model trials with 360 DF show that PM's final score has a good chance of being assessed as a full-time employee. This valuation model can change along with company policies in responding to internal and external changes.

References

Aggarwal, A., & Thakur, G. S. M. (2013). Techniques of performance appraisal-a review. International Journal of Engineering and Advanced Technology (IJEAT), 2(3), 617-621, https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=dfcb3490e4a5e999263339ef27d76548f1440410.

Anjomshoae, A., Hassan, A., & Wong, K. Y. (2019). An integrated AHP-based scheme for performance measurement in humanitarian supply chains. International Journal of Productivity and Performance Management, 68(5), 938–957, https://doi.org/10.1108/IJPPM-04-2018-0132.

Chen, M., Xie, L., & Su, H. (2021). Detection and location of model-plant mismatch in multiple input multiple output systems under model predictive controller using granger causality method. Processes, 9(11), https://doi.org/10.3390/pr9111976.

Circular Letter of the Minister of SOEs No. 7, Pub. L. No. SE-7/MBU/Q7/2020, 3 (2020).

Daniali, S. M., Barykin, S. E., Khortabi, F. M., Kalinina, O. V., Tcukanova, O. A., Torosyan, E. K., Poliakova, S., Prosekov, S., Moiseev, N., & Senjyu, T. (2022). An Employee Competency Framework in a Welfare Organization. Sustainability, 14(4), 2397, https://doi.org/10.3390/su14042397.

Desiani, A., Primartha, R., Arhami, M., & Orsalan, O. (2019). Naive Bayes classifier for infant weight prediction of hypertension mother. Journal of Physics: Conference Series, 1282(1), 1–10, https://doi.org/10.1088/1742-6596/1282/1/012005.

Fitri, S. G., Selsi, R., Rustam, Z., & Pandelaki, J. (2020). Naïve bayes classifier models for cerebral infarction classification. Journal of Physics: Conference Series, 1490(1), 1–9, https://doi.org/10.1088/1742-6596/1490/1/012019.

Peraturan Pemerintah (PP) No. 35, Pub. L. No. 35 OF 2O2I, 42 (2021), https://peraturan.bpk.go.id/Home/Details/161904/pp-no-35-tahun-2021.

DPR. (2013). SOEs. House File, 18(1), 22–27, https://berkas.dpr.go.id/puskajianggaran/kamus/file/kamus-240.pdf.

Jayasena, N. S., Mallawaarachchi, H., & De Silva, L. (2020). Environmental sustainability of facilities management: Analytical hierarchy process (AHP) based model for evaluation. Built Environment Project and Asset Management, 10(2), 261–276, https://doi.org/10.1108/BEPAM-12-2018-0157.

Kanaslan, E. K., & Iyem, C. (2016). Is 360 Degree Feedback Appraisal an Effective Way of Performance Evaluation?. International Journal of Academic Research in Business and Social Sciences, 6(5), 172–182, https://doi.org/10.6007/ijarbss/v6-i5/2124.

Khristiningrum, V. A., Gustomo, A., & Ginting, H. (2021). Strengthening Human Capital Department Roles through Building Collaboration with External Stakeholders. The Asian Journal of Technology Management (AJTM), 14(2), 192–204, https://doi.org/10.12695/ajtm.2021.14.2.6.

Kurniawan, Y. I., Cahyono, T., Nofiyati, Maryanto, E., Fadli, A., & Indraswari, N. R. (2020). Preprocessing Using Correlation Based Features Selection on Naive Bayes Classification. IOP Conference Series: Materials Science and Engineering, 982(1), 1–9, https://doi.org/10.1088/1757-899X/982/1/012012.

Lanz, J. J., Gregory, P., & Harmon, L. (2021). Assessing Physician Performance Using 360-degree Multisource Surveys: Do Biases Exist Due to Gender, Country of Training, Native Language, and Age? Diversity and Equality. in Health and Care, 18(9), 451–456, https://doi.org/10.21203/rs.3.rs-69954/v2.

Laurentia, N. T., & Septiani, W. (2021). YPBM University Tourism Building Location Selection with a Combination of Cut off Point and AHP Topsis Method. EasyChair Preprint 4940, 1–7, https://wvvw.easychair.org/publications/preprint_download/qdlZ.

Lou, N. M., So, A. S. I., & Hsieh, Y. J. (2019). Integrated resort employee competencies: a Macau perspective. International Journal of Contemporary Hospitality Management, 31(1), 247–267, https://doi.org/10.1108/IJCHM-07-2017-0431.

Marinda, V. S. (2021). Organizational Culture, Emotional Intelligence and Motivation: Its Effect on Organizational Citizenship Behavior (OCB) on Employees of State-Owned Enterprises in Indonesia. Turkish Journal of Computer and Mathematics Education, 12(8), 1342–1348, https://turcomat.org/index.php/turkbilmat/article/view/3153.

Odysseas Kopsidas. (2021). The 360-Degree Feedback Model as a Tool of Total Quality Management. Economics World, 9(1), https://doi.org/10.17265/2328-7144/2021.01.001.

Pipatprapa, A., Huang, H. H., & Huang, C. H. (2018). Enhancing the effectiveness of AHP for environmental performance assessment of Thailand and Taiwan’s food industry. Environmental Monitoring and Assessment, 190(12), https://doi.org/10.1007/s10661-018-7113-5.

Sanhueza, K. S., & Nikulin, C. (2019). A framework for design methods, models and techniques for product and process development: A novel classification to increase their applicability in practices. Business Process Management Journal, 25(7), 1759–1782, https://doi.org/10.1108/BPMJ-08-2018-0216.

Schuller, R. H. (2020). Nurturing an organization’s high achievers through strategic talent development: An asymmetric approach to talent management investment. Strategic Direction, 36(3), 28–30, https://doi.org/10.1108/SD-12-2019-0236.

Shen, Y., Li, Y., Zheng, H. T., Tang, B., & Yang, M. (2019). Enhancing ontology-driven diagnostic reasoning with a symptom-dependency-aware Naïve Bayes classifier. BMC Bioinformatics, 20(1), 1–15, https://doi.org/10.1186/s12859-019-2924-0.

SOE Minister Regulation No.7, Pub. L. No. PER-7/MBU/09/2022, 1 (2022).

SOEs, K. (2022). SOEs for Indonesia, https://bumn.go.id/responsible/program/bumn-untuk-indonesia-sn.

Vantilborgh, T., & Permans, R. (2013). Adding value with learning agility: How to identify and develop high-potential employees. Development and Learning in Organizations, 27(5), 24–26, https://doi.org/10.1108/dlo-07-2013-0043.

Yin, C., & McKay, A. (2018). Model verification and validation strategies and methods: An application case study. ISCIIA and ITCA 2018 - 8th International Symposium on Computational Intelligence and Industrial Applications and 12th China-Japan International Workshop on Information Technology and Control Applications, https://eprints.whiterose.ac.uk/135648/.

Zakaria, M. R., & Putra, Y. H. (2018). Employee Performance Appraisal to DeterMine Best Engineer Candidates with Analytical Hierarchy Process Approach. IOP Conference Series: Materials Science and Engineering, 407(1), https://doi.org/10.1088/1757-899X/407/1/012169.

Zayum, S. (2017). Performance Appraisal and Employee Productivity in Plateau State Internal Revenue Service, Nigeria. Journal of Public Administration and Governance, 7, 15, https://doi.org/10.5296/jpag.v7i4.11973.