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Autonomous Cognitive Leveling Game Pada Serious Game Menggunakan Particle Swarm Optimization Eko Subiyantoro; Azhari Azhari
Jurnal Buana Informatika Vol. 8 No. 2 (2017): Jurnal Buana Informatika Volume 8 Nomor 2 April 2017
Publisher : Universitas Atma Jaya Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24002/jbi.v8i2.1080

Abstract

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 
Pengembangan “RPP Generator” Menggunakan Metode Text Mining Untuk Meningkatkan Keterampilan Guru SMK Dalam Menyusun RPP K-13 Eko Subiyantoro
Jurnal Kewidyaiswaraan Vol 4 No 2 (2019): Jurnal Kewidyaiswaraan
Publisher : Pusat Pembinaan Jabatan Fungsional Bidang Pengembangan Kompetensi Pegawai ASN

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (3773.394 KB)

Abstract

Based on Permendikbud Number 22 two thousand and sixteen, it is stated that every teacher in the education unit is obliged to prepare a Learning Implementation Plan (RPP) in a complete and systematic manner. So that each teacher is required to prepare and prepare an integrated and integrative Learning Implementation Plan. Unfortunately, not a few teachers have difficulties in determining the RPP model that really fits the needs of students. This study offers a software application that is able to analyze Basic Competencies (KD), matching suitable learning models, and integrating in the RPP format in accordance with the applicable provisions. Text mining methods are used to analyze the linearity of KD3 - KD4 and recommendations for learning models based on Operational Words (Revised Bloom's Taxonomy KKO, Dave-Simpson). While the application development model uses the Analysis, Design, Develop, Implement, and Evaluation (ADDIE) development methods that are integrated with the prototype development model at the design stage. The results of this study produce desktop-based RPP Generator software that can assist teachers in preparing K-13 lesson plans. The feasibility testing of this software includes the testing of material experts, media experts, and teachers obtained percentages with an average of 95.8%, thus the RPP Generator software can be used by teachers in making systematic K-13 RPP.