NOVRIZAL, KEVIN (2025) Q-LEARNING UNTUK PENYESUAIAN LEVEL DINAMIS PADA GAME KARTU UNITY UNTUK ANAK BERKEBUTUHAN KHUSUS. S1 thesis, Universitas Mercu Buana Jakarta.
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Abstract
This research develops an educational card-based game using the Q-Learning algorithm to dynamically adjust difficulty levels, specifically designed for children with special needs. In this game, the system adapts the game level based on player performance metrics such as score, completion time, and the number of correct or incorrect answers. This approach aims to create an adaptive learning experience, where game challenges are automatically aligned with each player’s cognitive abilities. The study employs a quantitative approach to assess the effectiveness of the Q-Learning algorithm in automatically adjusting difficulty levels. Data is collected through game logs that record children's performance in each session. Data analysis is conducted to evaluate the system's success in providing a responsive and supportive learning experience. The results of this study indicate that the Q-Learning algorithm effectively adjusts game difficulty levels, potentially enhancing the cognitive skills of children with special needs. This research is expected to serve as a reference for the future development of adaptive educational applications. Keywords: Q-Learning, difficulty adaptation, educational game, children with special needs, adaptive learning. Penelitian ini mengembangkan permainan edukasi berbasis kartu dengan algoritma Q-Learning untuk menyesuaikan tingkat kesulitan secara dinamis, ditujukan bagi anak-anak berkebutuhan khusus. Dalam game ini, sistem menyesuaikan level permainan berdasarkan performa pemain, seperti skor, waktu penyelesaian, dan jumlah jawaban benar atau salah. Pendekatan ini bertujuan menciptakan pengalaman belajar yang adaptif, di mana tantangan permainan secara otomatis disesuaikan dengan kemampuan kognitif masing-masing pemain. Metode penelitian ini menggunakan pendekatan kuantitatif untuk mengukur efektivitas algoritma Q-Learning dalam menyesuaikan tingkat kesulitan secara otomatis. Data dikumpulkan melalui log permainan yang mencatat performa anak-anak dalam setiap sesi. Analisis data dilakukan untuk mengevaluasi keberhasilan sistem dalam memberikan pengalaman bermain yang responsif dan mendukung pembelajaran. Hasil penelitian ini menunjukkan bahwa algoritma Q-Learning dapat secara efektif menyesuaikan tingkat kesulitan permainan, yang berpotensi meningkatkan keterampilan kognitif anak-anak berkebutuhan khusus. Kontribusi penelitian ini diharapkan dapat menjadi acuan bagi pengembangan aplikasi edukasi adaptif di masa depan. Kata kunci: Q-Learning, adaptasi tingkat kesulitan, game edukasi, anak berkebutuhan khusus, pembelajaran adaptif.
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