Perbandingan Penggunaan
Social Learning
dan Tanpa
Social Learning
pada
Soccer Game Optimization
Tanpa
Subtitute Player
1)
Herlyn Anggraeni, 2) Hindriyanto Dwi Purnomo,3) Christine Dewi Program Studi Teknik Informatika
Fakultas Teknologi Informasi Universitas Kristen Satya Wacana Jl. Diponegoro 52-60, Salatiga 50711, Indonesia
Email:1)elyn_lyn17@yahoo.com, 2)hindriyanto_fti@yahoo.com, 3)christine_d_13@yahoo.com
Abstract
Soccer Game Optimization (SGO) is a new of Metaheuristic method that uses football player as its analogy. The method consist of two fundamental component, ‘move off’ and ‘move forward’. This research aims to compare the performance of Soccer Game Optimization using Social Learning and without Social Learning. The experiment result on 10 continuous benchmark problems show that the SGO without Social Learning perform better than the SGO with Social Learning.
Keywords: Metaheuristic, Soccer Game Optimization, Social Learning
Abstrak
Soccer Game Optimization (SGO) adalah satu metode Metaheuristic yang relatif baru. Metode ini menggunakan pergerakan dasar sebagai analoginya. Metode Soccer Game Optimization memiliki dua komponen dasar, move off dan move forward.
Penelitian ini membandingkan performa Soccer Game Optimization dengan Social
Learning dan tanpa Social Learning. Berdasarkan eksperimen didapatkan hasil SGO
tanpa Social Learning lebih baik daripada Soccer Game Optimization dengan Social
Learning.
