Meiliya Cahya Yustina, Ichwan Nul Ichsan, Galura Muhammad Suranegara

Implementasi Algoritma Genetika Proses Mutasi Differential Evolution Pada Sistem Penjadwalan Mata Pelajaran

Introduction

Implementasi algoritma genetika proses mutasi differential evolution pada sistem penjadwalan mata pelajaran. Atasi penjadwalan sekolah inefisien. Kembangkan sistem otomatis di SMAN 2 Purwakarta dengan Algoritma Genetika & Differential Evolution. Hasilkan jadwal optimal tanpa bentrok, layak pakai.

Abstract

Making schedules at SMAN 2 Purwakarta requires extra effort due to the large number of classes and teachers. The current scheduling system uses two different software namely Asc Timetables and Microsoft Excel. The use of both software is inefficient and error-prone. The two software cannot be connected to each other so that the creation of schedules must be separate and requires a lot of time in synchronization which has an impact on the quality of learning obtained by students. To overcome this problem, an integrated scheduling system is needed that can work automatically and efficiently in one system. This research aims to create a scheduling system that is made automatically with optimization methods. One of the optimization methods is Genetic Algorithm and Differential Evolution. The terminology used is the initial population, calculate fitness, selection, crossover, mutation and iteration. So that the implementation of the system in this study uses a genetic algorithm with a differential evolution mutation process. The method used is using the Software Development Life Cycle (SDLC) with a waterfall development model. The results of the application of the genetic algorithm with the differential evolution mutation process show that the schedule generation meets the limitations for more optimal results. The limitation is that there should be no schedule clashes between teachers in the same hours and days. Based on the test results using SUS, the system gets a score from the SUS calculation which is 69.1. From this score get the weight of the SUS Grade Scale score “B” and Adjective Rating “Good”. So that it requires further development on the system. However, with this category the system is feasible to use if based on SUS testing.

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