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All Journal J-SAKTI (Jurnal Sains Komputer dan Informatika) J-SAKTI (Jurnal Sains Komputer dan Informatika)
Pipit Puspitasari
FTI UKSW, Salatiga, Indonesia
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Energy

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Implementasi Algoritma Genetika Untuk Penjadwalan Sekolah (Studi Kasus: SMP Negeri 2 Wonosegoro) Pipit Puspitasari; Magdalena A. Ineke Pakereng
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 7, No 1 (2023): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v7i1.600

Abstract

The development of increasingly advanced technology can help in the work, so that it can be done more quickly and easily. One of them is scheduling subjects using genetic algorithms. Genetic algorithm is a technique to find the best solution from several solutions so that it gets the best results according to the stopping criteria if it has done 10 experiments and reached 100 generations. This study uses teacher data, subject data, and time. The results of the study provide a list of optimal schedules with the highest fitness score of 1, where teachers do not have teaching hours at the same time. The system can assist in solving existing problems, which can process data to carry out the scheduling process.
Implementasi Algoritma Genetika Untuk Penjadwalan Sekolah (Studi Kasus: SMP Negeri 2 Wonosegoro) Pipit Puspitasari; Magdalena A. Ineke Pakereng
J-SAKTI (Jurnal Sains Komputer dan Informatika) Vol 7, No 1 (2023): EDISI MARET
Publisher : STIKOM Tunas Bangsa Pematangsiantar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30645/j-sakti.v7i1.600

Abstract

The development of increasingly advanced technology can help in the work, so that it can be done more quickly and easily. One of them is scheduling subjects using genetic algorithms. Genetic algorithm is a technique to find the best solution from several solutions so that it gets the best results according to the stopping criteria if it has done 10 experiments and reached 100 generations. This study uses teacher data, subject data, and time. The results of the study provide a list of optimal schedules with the highest fitness score of 1, where teachers do not have teaching hours at the same time. The system can assist in solving existing problems, which can process data to carry out the scheduling process.
Co-Authors Magdalena A. Ineke Pakereng Magdalena Ariance Ineke Pakereng