SISTEM INFORMASI PENJADWALAN SHIFT KERJA KARYAWAN MENGUNAKAN ALGORITMA GENETIKA (Studi Kasus Jawara Digital Art Store Yogjakarta)

Mustofa, Jihan (2020) SISTEM INFORMASI PENJADWALAN SHIFT KERJA KARYAWAN MENGUNAKAN ALGORITMA GENETIKA (Studi Kasus Jawara Digital Art Store Yogjakarta). Tugas Akhir thesis, University of Technology Yogyakarta.

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Abstract

Jawara Digital Art Store (JDA Store) is a local business in Yogyakarta Indonesia, which started in November 2009. JDA is experienced a problem in determining employee work shift scheduling where there are still many schedule collisions in preparing the work shift schedule itself. The step which is taken is to build an employee shift scheduling system that is automatic and according to the criteria and minimizes the clash of schedules that often occur when composing, where scheduling employee work shifts is an effect on employee productivity in achieving a predetermined target. Therefore. we need an employee work shift scheduling system that uses a Genetic Algorithm. The use of a Genetic Algorithm is intended so that the scheduling results are naturally arranged by the system through several calculation iterations. It can help employees, especially the management section, in arranging employee work shift schedules effectively and accurately by using a Genetic Algorithm. In this design the writer uses the PHP programming language and uses the CodeIgniter framework with MySQL DBMS as the database server, and Sublime Text 3 as a programming support tool. After tested, the results obtained in the first test with an initial mutation rate of 0.2 and a generation limit of 5000 result in the highest fitness value of 1623 with a 67.12% suitability level with an execution time of 2 minutes 46 seconds in generations 5000 and above. While tested with an initial mutation rate value of 0.4 and a generation limit of 50000, tt produces the highest fitness value of 1644 with a 67.99% suitability level with an execution time of 31 minutes 25 seconds in the 50000 generation and above. Keywords: System, JDA store, Scheduling, Genetic Algorithm, Shift.

Item Type: Thesis (Skripsi, Tugas Akhir or Kerja Praktek) (Tugas Akhir)
Subjects: T Technology > T Technology (General)
Divisions: Fakultas Sains Dan Teknologi > S1 Informatika
Depositing User: Kaprodi S1 Informatika UTY
Date Deposited: 13 Oct 2020 03:02
Last Modified: 13 Oct 2020 03:02
URI: http://eprints.uty.ac.id/id/eprint/5763

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