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All Journal Akiratech
Restu Imam Safii
Politeknik Negeri Jember
Computer Science & IT Control & Systems Engineering Electrical & Electronics Engineering Energy Engineering

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AI System Design for Modern Batik Pattern Generation Based on Progressive Growth of Generative Adversarial Networks (PGGAN) with the Integration of Jember Local Wisdom Restu Imam Safii; Denny Trias Utomo; Nitin; Sulistiyanto
Akiratech Vol. 3 No. 3 (2026)
Publisher : CV. Akira Java Bulu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.63935/akiratech.v3i3.292

Abstract

Batik is an Indonesian cultural heritage that has deep aesthetic and philosophical value. In Jember Regency, the Labako batik motif is a unique visual identity that represents agrarian culture through the symbol of tobacco leaves. Although Deep Learning  technologies such as Deep Convolutional Generative Adversarial Networks (DCGAN) have been used for motif generation, the model has limitations in producing high-resolution images with complex details consistently. This research aims to design an artificial intelligence system based on the Progressive Growing of Generative Adversarial Networks (PGGAN) to produce modern batik patterns that integrate Jember's local wisdom. The system development method used is the Spiral Model which includes the planning, risk analysis, development, and evaluation stages. This system is designed using the Next.js  framework for the user interface and MySQL as a database management system to store assets and order information. The result of this research is in the form of a system architecture design and workflow that is able to progressively increase image resolution starting from $16 \times 16$ pixels to $2000 \times 2000$ pixels. This design is expected to be a technical foundation in the development of digital platforms that are able to preserve local culture through generative technological innovation.
Co-Authors Denny Trias Utomo, Denny Trias Nitin Sulistiyanto, Sulistiyanto