OPTIMASI PENJADWALAN KEGIATAN BELAJAR MENGAJAR MENGGUNAKAN ALGORITMA GENETIKA (STUDI KASUS : SMKN 8 MALANG)

GUSTI, DANI ARIANTO (2017) OPTIMASI PENJADWALAN KEGIATAN BELAJAR MENGAJAR MENGGUNAKAN ALGORITMA GENETIKA (STUDI KASUS : SMKN 8 MALANG). Sarjana thesis, Sekolah Tinggi Informatika dan Komputer Indonesia(STIKI) MALANG.

	Text ABSTRAK.docx Download (15kB)
	Text BAB I.doc Download (85kB)
	Text BAB V.docx Download (30kB)

Abstract

Keywords : scheduling optimization, artificial intelligent, genetic algorithms. Artificial Intelligent an artificial intelligence engine that resembles the behavior performed by human beings, one of the methods contained in Artificial Intelligent is a method of genetic algorithms. Genetic algorithm is a search technique with a variety of data is done by generating a number of solutions or known as a population. It is also experienced by SMKN 8 Malang, where data subjects each semester is always diverse and generates quite a lot of data, taking into account the time and diverse class to establish a time schedule of teaching with the best combination. In using a genetic algorithm method must first obtain an initial population that its future will be calculated fitness value. If you already generated a fitness value, then do the formation of a new population or the new generation with the calculation of 20% elitism, 70% crossover (crossover), 10% mutation, the process will be conducted to find the fitness value of 1 or fitness value converges. If it had been obtained by the calculation, the time resource scheduling process has been completed.

Item Type:	Thesis (Sarjana)
Subjects:	Applied computing > Education
Divisions:	Engineering Sciences
Depositing User:	Unnamed user with username editor_perpustakaan
Date Deposited:	16 Aug 2019 06:56
Last Modified:	01 Oct 2024 09:40
URI:	http://repository.stiki.ac.id/id/eprint/350

Actions (login required)

View Item