A Systematic Literature Review of Employee Performance Appraisal Decision Support System
DOI:
https://doi.org/10.57096/edunity.v4i6.406Keywords:
decision support system, employee performance, literature reviewAbstract
Employees in an agency or company are the most important assets that affect the progress of a company, so there is a need to improve the quality of employee performance. Employee performance is an achievement achieved by an employee in carrying out work in accordance with the standards or criteria set in the company. The need for employee performance is important in an agency or company because it is related to a decision-making system for the company. This study aims to analyze the practice of decision-making systems for employee performance assessment. The method used in writing this article is literature review. The results of the study show that important indicators or criteria are considered in determining the weight of employee assessments. The methods of a Decision Making System (SPK) are very diverse to support the ranking and determinants of employee assessment decisions. Based on the literature review above, the author argues that the decision support system in assessing the best employee performance is with the Simple Additive Weighting (SAW) algorithm. This is supported by the assessment criteria used, including work performance, loyalty, initiative, responsibility, cooperation, communication, discipline, obedience and leadership. These criteria are often used in research to assess employee performance and produce a decision related to human resources that can be used by leaders in determining their company goals.
References
Andriani, S., & Meiriza, A. (2021). Application of the Simple Multi Attribute Rating Technique method in the provision of annual employee bonuses. Journal of Informatics and Information Systems Engineering, 7(3), 666–681. https://doi.org/10.28932/jutisi.v7i3.4079
Anggara, E. D., Widjaja, A., & Suteja, B. R. (2022). Performance Prediction as a Recommendation for Group Increase with Decision Tree and Logistic Regression. Journal of Informatics and Information Systems Engineering, 8(1), 218–234. https://doi.org/10.28932/jutisi.v8i1.4479
Aprilianti, L., Negoro, D. A., Meria, L., & Sofyan, J. F. (2023). The Effect of Work Stress and Motivation on Employee Performance by Mediating Job Satisfaction Variables. Journal of Business and Management, 3(4), 762–772.
Arisantoso, Sadikin, N., Fatih, A., & Sanwasih, M. (2021). Decision Support System in Assessing the Best Employee Performance with Simple Additive Weighting (SAW) Algorithm. JURIKOM (Journal of Computer Research), 8(4), 135–140. https://doi.org/10.33050/tmj.v9i1.2210
Christiana, A. D., & Mailoa, E. (2022). Website-Based Employee Performance Appraisal Decision Support System Using the TOPSIS Method. AITI (Journal of Information Technology), 19(1), 31–47. https://doi.org/10.24246/aiti.v19i1.31-47
Gunawan, W., & Firmansyah, M. R. (2020). Monitoring and Evaluation of Employee Performance using Simple Additive Weighting and Hungarian Algorithms. ILKOM Scientific Journal, 12(2), 87–95. https://doi.org/10.33096/ilkom.v12i2.519.87-95
Kirana, C. A. D., & Harahap, A. S. (2022). Decision Support in the Assessment of Non-Civil Servant Government Employees using the Entropy Method. JURIKOM (Journal of Computer Research), 9(1), 159–166. https://doi.org/10.30865/jurikom.v9i1.3846
Lemantara, J., Suprianta, I. K. A., Arsyanti, L. A., & Lago, O. D. (2023). Increasing the efficiency of employee selection time by combining the analytical hierarchy process and simple increasing weighting methods. Journal of Information Technology and Computer Science (JTIIK), 10(3), 561–572. https://doi.org/10.25126/jtiik.2023106654
Nasution, M. I., Fadlil, A., & Sunardi. (2021). Comparison of Smart and Deadly Methods for Employee Selection at Merapi Online Corporation. Journal of Information Technology and Computer Science (JTIIK), 8(6), 1205–1214. https://doi.org/10.25126/jtiik.2021863583
Rahman, A. M. (2024). Decision Support System by Applying the WASPAS Method and ROC Weighting in Employee Performance Assessment. JURIKOM (Journal of Computer Research), 11(4), 128–137. https://doi.org/10.30865/jurikom.v1i4.8471
Roza, Y. F., & Triase. (2024). Implementation of ROC and CPI Methods in the Selection of New Employees at PT. Neora Infrastructure Indonesia. Systematics, 13(4), 1571–1586.
Rumui, N., Sakinah, N., Niah, C. N. R., & Rumalutur, F. (2024). Application of the Weighted Product (WP) Method in the Employee Acceptance Decision Support System at Dewata Store Fakfak. Journal of Information Technology and Computer Science (JTIIK), 11(6), 1335–1344. https://doi.org/10.25126/jtiik.2024118739
Sanjaya, R., & Nataliani, Y. (2021). Comparison of Criterion Weighting and Criterion Selection in Employee Performance Grouping with Fuzzy C-Means. Journal of Informatics Science, 12(1), 1–10. https://doi.org/10.24002/jbi.v12i1.4341
Setiawan, W., Pranoto, N., & Huda, K. (2020). Employee Performance Evaluation Decision Support System with the SMART Method (Simple Multi Attribute Rating Technique). Journal of RESTI (Systems Engineering and Information Technology), 4(1), 50–55. https://doi.org/10.29207/resti.v4i1.1384
Sunardi, Umar, R., & Nasution, D. S. (2022). Analysis of employee performance appraisal using the WASPAS method. JURIKOM (Journal of Computer Research), 9(3), 697–704. https://doi.org/10.30865/jurikom.v9i3.4168
Syaputra, N., & Kusuma, M. (2021). The Effect of Motivation, Job Satisfaction and Work Stress on Employee Performance at PT. Agung Automall Bengkulu. Ekombis Review: Scientific Journal of Economics and Business, 10(1), 432–442. https://doi.org/10.37676/ekombis.v10i1.1682
Yuminah, Umar, R., & Fadlil, A. (2020). Analysis of AHP and Promethee Methods on Decision Support System for Employee Soft Skills Competency Assessment. Journal of Information Technology and Computer Science (JTIIK), 7(1), 27–36. https://doi.org/10.25126/jtiik202071118
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Ery Oktavianingrum, Ifah Rofiqoh

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under aCreative Commons Attribution-ShareAlike 4.0 International (CC-BY-SA). that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work.