Paper Title
Artificial Neural Network for Chicken Growth Anomaly Detection

Many broiler farming industry in Indonesia implement partnership schema. The schema should be accompanied by good monitoring system. Fast detection of chicken growth anomaly is needed. A model of artificial neural network is proposed to detect the anomalies of chicken growth. The model is based on the record of mortality number and feed conversion ratio from three consecutive days. The performa of the model is assessed using data from 10 periods of chicken growth. The experiment result reveals that the model is promising to detech the anomaly of chicken growth. Keywords - Chicken growth, anomaly detection, artificial neural network, feed conversion ratio, mortality number