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All Journal Techno.Com: Jurnal Teknologi Informasi Jurnal Buana Informatika Sistemasi: Jurnal Sistem Informasi Abdimas Galuh: Jurnal Pengabdian Kepada Masyarakat Jurnal Abdimas Ilmiah Citra Bakti (JAICB) Journal Of Information And Technology Unimor (JITU)
Maria Karmelia Fajarlestari
Universitas Pignatelli Triputra
Agriculture, Biological Sciences & Forestry Arts Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry Computer Science & IT Economics, Econometrics & Finance Electrical & Electronics Engineering Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Nursing Physics Social Sciences

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Journal : Jurnal Buana Informatika

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Sistem Penjadwalan Karyawan dengan Algoritma Genetika Fajarlestari, Maria Karmelia; Hardiyanti, Mawar
Jurnal Buana Informatika Vol. 15 No. 2 (2024): Jurnal Buana Informatika, Volume 15, Nomor 02, Oktober 2024
Publisher : Universitas Atma Jaya Yogyakarta

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Abstract

Employee scheduling is a complex problem in Human Resource Management (HRM) that significantly impacts operational efficiency. This study develops an employee scheduling system using a genetic algorithm. The employee schedules are constructed by considering scheduling rules and various components such as the number of days, shifts, employee quality, and scheduling requests. The genetic algorithm, proven effective in solving various optimization problems, is employed to generate optimal schedules through the processes of selection, crossover, and mutation. The results indicate that the genetic algorithm can effectively produce employee schedules, with fitness values indicating improved schedule quality as iterations increase. The findings of this study are anticipated to be useful in HRM, aiming to improve both employee efficiency and satisfaction.
Sistem Penjadwalan Karyawan dengan Algoritma Genetika Fajarlestari, Maria Karmelia; Hardiyanti, Mawar
Jurnal Buana Informatika Vol. 15 No. 2 (2024): Jurnal Buana Informatika, Volume 15, Nomor 02, Oktober 2024
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Employee scheduling is a complex problem in Human Resource Management (HRM) that significantly impacts operational efficiency. This study develops an employee scheduling system using a genetic algorithm. The employee schedules are constructed by considering scheduling rules and various components such as the number of days, shifts, employee quality, and scheduling requests. The genetic algorithm, proven effective in solving various optimization problems, is employed to generate optimal schedules through the processes of selection, crossover, and mutation. The results indicate that the genetic algorithm can effectively produce employee schedules, with fitness values indicating improved schedule quality as iterations increase. The findings of this study are anticipated to be useful in HRM, aiming to improve both employee efficiency and satisfaction.
Co-Authors Agustinus Kismet Nugroho Jati Bagas Dwi Yulianto Endang Purwaningsih Ignasius Boli Suban Mawar Hardiyanti