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All Journal Journal of Innovative and Creativity
Prasista Dhiyaul Haq
Universitas Muhadi Setiabudi
Education Languange, Linguistic, Communication & Media Mathematics Social Sciences Other

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Penerapan Vision Transformer Untuk Klasifkasi Sampah Rumah Tangga Prasista Dhiyaul Haq; Bambang Irawan
Journal of Innovative and Creativity Vol. 6 No. 1 (2026)
Publisher : Fakultas Ilmu Pendidikan Universitas Pahlawan Tuanku Tambusai

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31004/joecy.v6i1.7826

Abstract

The increasing volume of Household waste requires an accurate and efficient automatic waste sorting system. This study aims to apply Vision Transformer (ViT) for image-based household waste clasification. The dataset was divided inti training and validation sets and prepared to match the Vision Transformer archtecture. The ViT-Base Patch16-224 model was trained using the AdamW optimizer with a learning rate of 0.0002, batch size of 16, and 15 training epoch. Model performence was evaluated using accuracy, precision, recall, F1-score, and confusion matrix. Experimental results show that the proposed model achieved an overall accuracy of 95%. The inorganic class obtained a precision of 0.9, recall of 0.96, and F1-score of 0.95, while the organic class achived a precision of 0.94, recall of 0.93, F1-score of 0.94. these result indicate that self-attention mechanism in Vision Transformer effectively extracts global visual features and improves clasification stability. Therefore, Vision Transformer dermonstrates strong potential for implementasi in intelligent automatic waste sorting systems.
Co-Authors Bambang Irawan