Algoritma Anti-Bias Pasca-Prediksi pada Sistem Pengenalan Makanan Khas Yogyakarta Berbasis ESP32-CAM - Agus Siswoyo; Johannes Leon (Politeknik Negeri Lhokseumawe, 2026)
Automatic recognition of regional food specialties using embedded devices still faces challenges, particularly prediction imbalance (bias) due to the very small dataset size. This study developed a recognition system for eight types of Yogyakarta specialties (gudeg, sate klatak, bakpia, jogja tahu, pecel gudeg, ayam geprek, es dawet, and klepon) based on ESP32‑CAM integrated with a Flask server and a TensorFlow model (MobileNetV2). The training dataset consisted of only 51 images (average 6–7 images per class). The main problem encountered was extreme bias: the initial model predicted the