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Alam Rahmatulloh
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International Journal of Informatics and Computing
Published by Meta Pustaka Intelektual
ISSN : -     EISSN : 30904722     DOI : -
Core Subject : Science, Engineering,
Computer Science & IT Electrical & Electronics Engineering
International Journal of Informatics and Computing (JICO) is the official publication of the Institute of Advanced Informatics and Computing (IAICO). The journal is open to submission from scholars and experts in the wide areas of informatics and computing from the global world.
Arjuna Subject : Ilmu Komputer (semua kategori) - Ilmu Komputer (Lain-Lain)
Articles 12 Documents
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GANS: Genetic Algorithm and Neural Network Integration for Optimal Brain Selection in Snake Game Bambang Pudjoatmodjo; Mugi Praseptiawan; Ulka Chandini Pendit; Rusnida Romli
JICO: International Journal of Informatics and Computing Vol. 1 No. 2 (2025): November 2025
Publisher : IAICO

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Snake games have emerged as an engaging subject in artificial intelligence and optimization research due to the growing interest in developing autonomous agents capable of controlling the snake intelligently. This study presents a hybrid approach by integrating a Genetic Algorithm (GA) with a Neural Network (NN) to enhance the snake game’s performance, effectively forming an adaptive and intelligent control system or “brain.” In this framework, the Snake game is modeled as an optimization problem, where the GA is employed to optimize the parameters of the NN to improve the decision-making process of the snake. The GA operates by evolving a population of individuals each representing a set of strategies through selection, crossover, and mutation. These operations are iteratively applied to discover optimal solutions within the vast parameter space. The integrated neural network enables the snake to make real-time decisions based on environmental stimuli, enhancing its survival and goal-seeking behavior. Fitness evaluation is performed based on everyone’s gameplay performance, where the most successful individuals contribute to the next generation. Experimental results demonstrate that the combination of GA and NN significantly improves snake gameplay performance. The fitness score acts as a performance indicator, showing that higher-generation populations tend to yield better results. For instance, snakes trained over 100 generations achieved scores around 8, while those trained over 500 generations exceeded scores of 15. This confirms the effectiveness of evolutionary optimization in training neural networks for game-based AI tasks.
A Transform-Domain Robust Watermarking Model Using Discrete Wavelet Transform for Image Copyright Security Randi Rizal; Nazwa Auliarahman; Siti Rahayu Selamat; Mae B. Lodana
JICO: International Journal of Informatics and Computing Vol. 1 No. 2 (2025): November 2025
Publisher : IAICO

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This research presents the development of a Discrete Wavelet Transform (DWT)–based method designed to strengthen digital copyright protection in images. The proposed approach leverages multi-resolution decomposition to embed copyright information within high-frequency and mid-frequency sub-bands, enabling improved resistance against common image attacks such as compression, noise addition, and geometric manipulation. Experimental evaluation shows that the method maintains high imperceptibility, with minimal impact on visual quality, while achieving strong extraction accuracy under various distortion scenarios. The results confirm that DWT remains a reliable foundation for constructing secure and robust watermarking mechanisms suitable for modern digital content protection needs.

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