| dc.description.abstract | Rainfall variability during dry and rainy season affect variation in milk production at UPTD BPT SP & HMT Cikole in Lembang, West Java. Milk production rate during the dry season is higher compared to the rainy season. This is due to the quality of food consumed by the cows during the dry season is better than the rainy season. Analysis between rainfall data and milk production using linear regression analysis produces a relatively strong relationship shown by determination coefficient equal to 0,919, showing that the rainfall variability explains more than 90% of milk production. Distribution and variability of rainfall in Indonesia is influenced by El Nino Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) event, where both phenomena can be identified by using Ocean Nino Index (ONI) and Dipole Mode Index (DMI), respectively. Compared to DMI, ONI has a stronger relationship withrainfall and milk production at UPTD BPT SP & HMT Cikole, Lembang. ONI can be used to predict milk production in the rainy season and the dry season with a time lag of three months. The prediction model for milk production in the dry season is developed by using milk production data in JJA and rainfall data in MAM. For the rainy season, the prediction model uses pair of milk production data in DJF and rainfall data in SON.The relationship between seasonal ONI and milk production indicate a quadratic pattern, with a coefficient of determination around 92.8% and 34.3% in the rainy and dry season, respectively. | en |
