Bambang Sumintono
Universitas Islam International Indonesia

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Human–AI Co-Creation in Traditional Craft: Generative Artificial Intelligence for Batik Design Innovation in Indonesian Creative Communities Komarudin Kudiya; Bambang Sumintono; Saftiyaningsih Ken Atik
Glosains: Jurnal Sains Global Indonesia Vol. 7 No. 3 (2026): Glosains: Jurnal Sains Global Indonesia
Publisher : Sekolah Tinggi Agama Islam Kuningan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59784/glosains.v7i3.799

Abstract

Background: The declining generational renewal of batik designers poses challenges to sustaining innovation in Indonesia’s traditional craft industry. Objective: This study investigates how generative artificial intelligence can support human–AI co-creation in batikdesign innovation. Methods: Using a mixed-methods case study of a Batik AI training program organized by the Indonesian Batik Artisans and Entrepreneurs Association, this research examines the integration of AI-assisted design exploration within batikcreative communities. Data were collected through observations, documentation of AI-generated designs, and a perception survey involving 300 respondents from the batik ecosystem. Results: The results indicate that generative AI substantially expands the exploration of motif variations, enabling participants to generate 300 batik design simulations—200 in Cirebon and 100 in Bandung—featuring traditional motifs, including parang, kawung, and megamendung. Descriptive statistical analysis involving 300 respondents revealed positive perceptions across all dimensions. Motif composition received the highest score (mean = 4.24, SD = 0.68), followed by color sharpness (mean = 4.21), motif authenticity (mean = 4.18), color brightness (mean = 4.15), originality of motif ideas (mean = 4.11), and the quality of supplementary motifs (mean = 4.07). The philosophical meaning of the motifs received the lowest score (mean = 3.96), indicating the limitations of AI in encoding cultural symbolism. The instrument demonstrated satisfactory reliability (Cronbach’s alpha = 0.87). Conclusion: The findings suggest that generative AI functions as a collaborative tool that enhances the capacity for creative design exploration. However, respondents’ perceptions of the philosophical meaning of the motifs (mean = 3.96) indicate that human cultural curation remains indispensable for preserving the profound symbolic authenticity of traditional batik designs. These findings reflect respondents’ perceptions within the specific training contexts of Cirebon and Bandung.