Writing

Notes and research.

Published work and longer notes on Android, on-chain systems, and applied machine learning. Papers open with the abstract; everything else is a short read.

1 entry · 1 peer reviewed

ORCID record

AITI · Vol. 23, No. 1 · pp. 46–60 · 2026

Peer reviewed

Classification of Batik Keraton motifs using ResNet-50 fine-tuning architecture

Santosa, S. B., Chrismanto, A. R., & Susanto, B.

Fine-tuning a ResNet-50 to classify four Keraton batik motif classes, reaching 97.8% test accuracy. Published in AITI volume 23.

97.8%: test accuracy
96.8%: validation accuracy
4: motif classes
ResNet-50: fine-tuned

Read abstractdoi:10.24246/aiti.v23i1.46-60