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

Authors

  • Muhammad Muhardeny Universitas Indo Global Mandiri
  • Muhammad Haviz Irfani Universitas Indo Global Mandiri
  • Juhaini Alie Universitas Indo Global Mandiri

DOI:

https://doi.org/10.36982/jseci.v1i1.3047

Keywords:

scheduling, particle swarm optimization, waterfall

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

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Published

2023-06-08

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Articles