SISTEM PENDUKUNG KEPUTUSAN PEMBERIAN BONUS KARYAWAN MENGGUNAKAN METODE SIMPLE ADDITIVE WEIGHTING

Fahmi Prima Yasa; Ifan  Junaedi; Anton Zulkarnain  Sianipar

doi:10.46880/mtk.v12i2.5747

Authors

Fahmi Prima Yasa STMIK Jayakarta Indonesia
Ifan Junaedi STMIK Jayakarta
Anton Zulkarnain Sianipar STMIK Jayakarta

DOI:

https://doi.org/10.46880/mtk.v12i2.5747

Keywords:

Employee Bonus, SAW Method, Decision Support System (DSS), Performance Appraisal, Web-Based System, Multi-Criteria Decision Making (MCDM)

Abstract

Employee bonus allocation is one form of corporate appreciation for employee performance in supporting organizational goals. However, the bonus determination process, which is still carried out manually at a private company that is the object of this study, often leads to subjectivity and inaccuracy in decision-making. This study aims to design and build a Decision Support System (DSS) for employee bonus allocation using the Simple Additive Weighting (SAW) method. The SAW method is used for multi-criteria calculation through the weighting and ranking of alternatives. The system was developed as a web-based application using the PHP programming language and MySQL database, applying six assessment criteria: attendance, discipline, work quality/competence, teamwork, loyalty, and administrative violations. The research was conducted using the System Development Life Cycle (SDLC) waterfall model, consisting of requirement analysis, system design, implementation, and testing. The system was tested on 20 employee alternative data and was able to perform objective employee assessment and ranking based on the highest preference value, which was then mapped into four bonus-recommendation zone classifications. Black Box Testing on authentication security, data integrity, computational accuracy, and interface usability showed a 100% success rate with a 0% computational error margin, indicating that all system features functioned according to user requirements. With this system, the employee bonus determination process becomes more effective, transparent, and efficient.

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