Penjadwalan Mata Pelajaran Menggunakan Algoritma Particle Swarm Optimization (PSO) Pada SMPIT Mufidatul Ilmi

Muhammad Muhardeny, M. Irfani, Juhaini Alie
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引用次数: 1

Abstract

Scheduling has a division of time based on a work sequence arrangement plan in the form of a list or table of activities or an activity plan with a detailed division of implementation time which is very necessary in carrying out institutional/company business processes. It is important to note the complexity of the process in scheduling appropriate subjects from various perspectives, both teachers, students and classrooms. Provision of teacher teaching schedules based on abilities in the field of subjects, suitable time each semester is very important to consider for very complex schedule arrangements, the number of classrooms that can be used in teaching activities is relatively small, and preventing teacher teaching conflicts so that the need for optimization of eye scheduling lesson to be made. Furthermore, at the stage of application development using the Waterfall method. The purpose of this research is to build a lesson scheduling application at SMPIT Mufidatul Ilmi by applying the particle swarm optimization (PSO) algorithm to compile lesson schedules. Particle Swarm Optimization is a population-based algorithm that exploits individuals in search. In PSO the population is called a swarm and individuals are called particles. Each particle moves at a speed adapted from the search area and stores it as the best position ever achieved. Design analysis includes Use Case Diagrams, Activity Diagrams, Class Diagrams, Sequence Diagrams, Entity Relationship Diagrams (ERD). The results of this study provide several primary data (service) features, especially features to provide scheduling results from processing with the PSO algorithm
日程安排是基于工作顺序安排计划的时间划分,以活动列表或表的形式出现,或者活动计划具有详细的执行时间划分,这在执行机构/公司业务流程时非常必要。重要的是要注意从教师、学生和教室的不同角度安排适当科目的过程的复杂性。根据学科领域的能力提供教师教学时间表,每个学期的合适时间是非常重要的考虑因素,因为非常复杂的时间表安排,可用于教学活动的教室数量相对较少,防止教师教学冲突,因此需要优化眼睛调度课程。此外,在应用程序开发阶段使用瀑布方法。本研究的目的是利用粒子群优化(PSO)算法来编制课程表,以建立SMPIT multifidatul Ilmi的课程表应用程式。粒子群优化是一种基于种群的算法,它利用个体进行搜索。在粒子群算法中,群体被称为群体,个体被称为粒子。每个粒子的移动速度与搜索区域相适应,并将其存储为有史以来的最佳位置。设计分析包括用例图、活动图、类图、序列图、实体关系图(ERD)。本研究的结果提供了几个主要的数据(服务)特征,特别是提供PSO算法处理调度结果的特征
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