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All Journal Pixel : Jurnal Ilmiah Komputer Grafis SEMIRATA 2015 Jurnal Sains Matematika dan Statistika Sinkron : Jurnal dan Penelitian Teknik Informatika Theorems (The Original Research of Mathematics) Journal on Education Building of Informatics, Technology and Science Diklat Review : Jurnal manajemen pendidikan dan pelatihan Bearing : Jurnal Penelitian dan Kajian Teknik Sipil Management Studies and Entrepreneurship Journal (MSEJ) Bisman (Bisnis dan Manajemen): The Journal of Business and Management Jurnal Pengabdian kepada Masyarakat Nusantara ABDINE Jurnal Pengabdian Masyarakat Jurnal Teknologi Komputer dan Informasi TRIMAS: Jurnal Inovasi dan Pengabdian Kepada Masyarakat Jurnal Pengabdian Masyarakat Bangsa Jurnal Pengabdian Harapan Bangsa SLUMP TeS : Jurnal Teknik Sipil Journal Of Artificial Intelligence And Software Engineering Smart Dedication: Jurnal Pengabdian Masyarakat
Welly Desriyati
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Journal : Journal Of Artificial Intelligence And Software Engineering

 1 
Optimization of Employee Reward Schemes Using Genetic Algorithm: A Multi Criteria Performance Based Approach Urva, Gellysa; Desriyati, Welly
Journal of Artificial Intelligence and Software Engineering Vol 5, No 2 (2025): June
Publisher : Politeknik Negeri Lhokseumawe

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30811/jaise.v5i2.7105

Abstract

Employee reward distribution plays an important role in increasing motivation and retention. Conventional employee reward models often contain elements of subjectivity and do not reflect the overall contribution of employees. This can lead to unfairness and reduce work motivation. Traditional models in reward allocation often fail to incorporate a comprehensive evaluation of employee performance based on various criteria. This study develops a multi-criteria performance-based reward allocation model using Genetic Algorithm (GA) as an optimization approach. The model is designed to consider various performance indicators such as performance, attendance, tenure, and innovation in the process of fair and proportional bonus distribution. The optimization results show a very strong positive correlation (r = 0.99) between the employee's composite score and the amount of bonus allocated. In addition, the simulation of the evolution of fitness values shows a constant increase in both the average and the best values of the solution population, confirming the effectiveness of the genetic algorithm exploration and convergence process. This model produces a bonus distribution that is proportional to employee contributions, reflecting the principles of fairness, meritocracy, and transparency in the reward system. In addition, this model is flexible to budget changes and can be replicated for real implementation. The scientific contribution of this research lies in the application of a heuristic approach to multi-criteria optimization in the context of human resource management, complementing the literature that has so far been dominated by linear models.
Co-Authors Abrar, Aidil Adelia Alfama Zamista Ahmad Fauzan Aidila Sari Aji Santoso Andanu, Surya Laksa Arta Rusidarma Putra Azis, Azwan Desyanti Desyanti Faisal, Rudi Fajar Mahmud, Sony Febrina Sari Gellysa Urva Halimatusadiyah Halimatusadiyah, Halimatusadiyah Hanifatul Rahmi Hanifatul Rahmi Herdian Tofani Irma Nurmala Dewi Jaya, Rizki Bagas Dwi Julanos Julanos Julanos, Julanos Khairul Azmi Marselin, Randi Mashadi Mashadi Mesran, Mesran Poltak Rinaldo T Putra, Sony Adiya Rahmi, Hanifatul Rika Ahdani Siregar Saputra, Juni Sari, Febrina Sellyana, Ari SIRLYANA, SIRLYANA Sri Gemawati Sri Sukmawati Sri Sukmawati Srihandayani, Susy Syahputra, Bayu Syamsiar, Syamsiar T Haykal Namdzulhajjri Thania Putri Salsabila Tri Handayani Winanda, Amar Yuliati , Tri Yuliati, Tri Yusrizal Yusrizal zakia, Zakia