Forecasting Duck Egg Production Using ARIMA Model: A Case Study on Magelang Ducks

This study investigated the application of the ARIMA model to forecast egg production trends in the Magelang ducks. Data were collected from 100 ducks over a 135-day period135 d of monitoring. The mean Daily Duck Production (DDP) was 43.53% with a standard deviation of 23.82%, indicating substantial variability in age-related traits and genetic factors. Following confirmation of data stationarity, the ARIMA (2,1,0) model was identified as the optimal fit. The model effectively captures historical trends and provides accurate forecasts of future production. The mathematic model was Y t = 0,896+0,322 Y t-1 +0,315 Y t-2 – 0,363 Y t-3 + ε t . These findings provide valuable insights into improving farm management, optimizing resource allocation, and enhancing egg production strategies. Thus, the ARIMA model can be used by researchers or farm managers to help farmers optimize resource management. This model helps farmers optimize resource management during peak and low production periods, making it highly useful even with limited data. Broadly, it enables better decision-making regarding feeding, breeding, and resource allocation for sustainable and profitable farm management.