Web-based employee reward determination system using Analytical Hierarchy Process (AHP)
Abstract
This study develops a web-based employee performance evaluation system using the Analytical Hierarchy Process (AHP) method to overcome the problem of inaccuracy and unfairness in reward giving at PT Transcosmos Commerce. The system is designed using an Agile approach with the Django framework and SQLite database. The AHP method is applied to calculate the weight of the assessment criteria (discipline, responsibility, productivity, work quality, and cooperation) through pairwise comparisons, resulting in a consistency ratio (CR) value of 0.08 less than 0.1, which indicates acceptable consistency. The results of the AHP calculation show that the highest criterion weight is Productivity (0.32), followed by Work Quality (0.25), Responsibility (0.18), Cooperation (0.15), and Discipline (0.10). The final employee score is obtained by combining the criteria weight and alternative values, with the highest scores obtained by employees A1 (Dani) of 0.42, A2 (Farhan) of 0.35, and A3 (Freya) of 0.23. System testing has proven an increase in evaluation time efficiency of 60 percent compared to manual methods, as well as reducing the subjectivity of assessments. The system also provides visualization of results in the form of graphs and automatic reports, facilitating managerial decision-making.
Keywords: AHP, criteria weighting, evaluation of performence, employee reward, Web Based System.Full Text:
PDFReferences
P. Zandi, M. Ajalli, and N. S. Ekhtiyati, “An extended simple additive weighting decision support system with application in the food industry,” Decis. Anal. J., vol. 14, p. 100553, 2025, doi: https://doi.org/10.1016/j.dajour.2025.100553
S. Sumardiono, “Development of Smart Villages through Electronic Population Census in Kalimati Village, Jatibarang District,” Gema Wiralodra, vol. 15, no. 2, pp. 37–41, 2024. https://doi.org/10.31943/gw.v15i2.694
W. Erfisal and L. Fimawahib, “Development of a Web-Based Learning Media for Social Studies Subject at Kepenuhan Hulu Junior High School (SMP),” RJOCS (Riau J. Comput. Sci., vol. 9, no. 1, pp. 58–65, 2023. https://doi.org/10.30606/rjocs.v9i1.1762
R. Wahyuni and Y. Irawan, “Web-Based Employee Performance Evaluation System at PT. Wifiku Indonesia,” J. Softw. Eng. Inf. Syst., vol. 1, no. 1, pp. 1–8, 2021. https://doi.org/10.37859/seis.v1i1.1777
S. Sumardiono, N. Ismail, J. Shadiq, Z. Q. Nida, S. Solikin, and R. Suryani, “Web-Based Decision Support System for Selecting Exemplary Teachers using TOPSIS Method,” Appl. Inf. Syst. Manag., vol. 8, no. 1, pp. 89–94, May 2025. https://doi.org/10.15408/aism.v8i1.45488
M. A. Prawira and R. Amin, “Decision Support System for Selecting the Best Employee at PT. Citra Prima Batara Using the AHP Method,” Jurnal Sains dan Teknologi ISTP, vol. 8, no. 1, 2022. https://doi.org/10.31294/jtk.v8i1.11641
Sumardiono, “Design of an Employee Evaluation System (E-Result) Using the Waterfall Model at XYZ University,” TEKNOSAINS, vol. 8, pp. 45–53, 2021. Doi: https://doi.org/10.37373/tekno.v8i1.76
S. Purba Dan Ruth Meivera Siburian and A. P. K. K. D. M. G. R. S. B. W. P. P. T. K. C. Medan, “Web-Based Employee Performance Evaluation Application Using the Graphic Rating Scale Method at PT. Tri Karya Cemerlang Medan,” J. Sains dan Teknol. ISTP, vol. 20, no. 02, pp. 199–210, 2024. Doi: https://doi.org/10.59637/jsti.v20i02.372
L. Lai, “Research and Design of Data Security Risk Assessment Model Based on Fusion of Deep Learning and Analytic Hierarchy Process (AHP),” Procedia Comput. Sci., vol. 262, pp. 747-756, 2025, doi: https://doi.org/10.1016/j.procs.2025.05.107
R. Rikky and H. Septanto, “Design of a Web-Based Performance Evaluation Application for Outstanding Employee Recommendation Using the Profile Matching Method at PT. ABC,” Inf. Syst. Educ. Prof. J. Inf. Syst., vol. 9, no. 1, p. 1, 2024. https://doi.org/10.51211/isbi.v9i1.2718
R. Gunawan, N. N. Alamsyah, and D. Darmansyah, “Web-Based Decision Support System for Employee Performance Evaluation Using the Weighted Product Method,” J-SISKO TECH (Jurnal Teknol. Sist. Inf. dan Sist. Komput. TGD), vol. 6, no. 1, p. 205, 2023. https://doi.org/10.53513/jsk.v6i1.7414
Y. K. Dwivedi, A. Sharma, N. P. Rana, M. Giannakis, P. Goel, and V. Dutot, “Evolution of artificial intelligence research in Technological Forecasting and Social Change: Research topics, trends, and future directions,” Technol. Forecast. Soc. Change, vol. 192, no. April, p. 122579, 2023. https://doi.org/10.1016/j.techfore.2023.122579
J. M. P. Kevin P. Gaffney, Martin Prammer, Larry Brasfield, D. Richard Hipp, Dan Kennedy, “SQLite,” Mob. Forensics - File Format Handb. Common File Formats File Syst. Used Mob. Devices, vol. 15, no. 12, pp. 129–155, 2022. https://doi.org/10.1007/978-3-030-98467-0_5
J. Swacha and A. Kulpa, “Evolution of Popularity and Multiaspectual Comparison of Widely Used Web Development Frameworks,” Electron., vol. 12, no. 17, 2023. https://doi.org/10.3390/electronics12173563
D. A. W. Prapto, R. Sipahutar, and M. Purwaningsih, “Web-Based Decision Support System for Best Employee Selection in Government Institutions using Analytical Hierarchy Process (AHP) Method,” Sistemasi, vol. 13, no. 3, p. 889, 2024. https://doi.org/10.32520/stmsi.v13i3.2796
DOI: https://doi.org/10.21107/simantec.v14i1.30276
Refbacks
- There are currently no refbacks.
Copyright (c) 2025 Sumardiono Sumardiono, Fajar Maulana
Indexed By
.png)

11.png)



