z-logo
open-access-imgOpen Access
Autonomous Cognitive Leveling Game Pada Serious Game Menggunakan Particle Swarm Optimization
Author(s) -
Eko Subiyantoro,
Azhari Azhari
Publication year - 2017
Publication title -
jurnal buana informatika
Language(s) - English
Resource type - Journals
eISSN - 2089-7642
pISSN - 2087-2534
DOI - 10.24002/jbi.v8i2.1080
Subject(s) - particle swarm optimization , computer science , artificial intelligence , cognition , humanities , psychology , machine learning , art , neuroscience
Abstract. Serious games containing the pedagogical aspects and as part of the device/media e-learning support the learning process. Besides, the learning method uses the game are better than the conventional learning, because learning materials that involve animation in the game will enable long-term memory of students. Particle swarm optimization (PSO) method offers a search procedure based on a population consisting of individuals called particles that change their position with respect to time. PSO, by way of initializing the position and velocity of a particle, calculates the fitness function of the solution and updates the position and velocity of a particle to a stop condition are found. The design of PSO on the problem of autonomous cognitive levels of the game on a serious game with a permutation is proposed by using the fitness function the distance between xi+1 (cognitive level game) with xi (cognitive pre-test). The expected outcome of this research is the sequence of levels completed in accordance with the needs of the learner.Keywords: Serious game, cognitive, pso Abstrak. Serious game sangat mendukung proses pembelajaran melalui permainan yang mengandung aspek pedagogis dan merupakan bagian dari alat/media e-learning. Selain itu metode pembelajaran menggunakan permainan lebih baik dibandingkan dengan pembelajaran konvensional, karena animasi materi pembelajaran dalam permainan akan mengaktifkan ingatan jangka panjang siswa.Metode particle swarm optimization (PSO) menawarkan suatu prose­dur pen­­ca­rian berdasar pada populasi yang terdiri atas individu-individu yang di­se­but par­­tikel, mengubah posisi mereka terhadap waktu. PSO dengan cara melakukan inisialisasi posisi dan kecepatan particle, menghitung fungsi fitness dari solusi dan mengupdate posisi dan kecepatan particle sampai kondisi berhenti ditemukan.Perancanagan PSO pada permasalahan autonomus cognitive level game pada serious game diusulkan menggunakan permutasi dengan fungsi fitness jarak antara xi+1(cognitive level game) dengan xi (cognitive pre-test).Hasil yang diharapkan dari penelitian ini adalah adanya urutan level game yang sesuai dengan kebutuhan pembelajar.Kata Kunci: Serious game, cognitive, pso

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here