Small Area
Estimation (SAE) is a statistical technique to estimate parameters of sub-population containing small size of
samples with adequate precision. This technique is very important to be developed due to the increasing needs of statistic for small domains, such as districts or villages. Some SAE techniques have been developed in Canada, USA, and UE based on real data. We adapted this technique to produce small area statistic in Indonesia based on national data collected by the Central Bureau of Statistic. We found that the linear model applied to auxiliary data produced estimates with low precision. In this paper we propose a class of
generalized additive mixed model to improve the model of auxiliary data in small area
estimation.