Proceedings of the 1st International Conference on Statistics and Analytics, ICSA 2019, 2-3 August 2019, Bogor, Indonesia

Research Article

Estimating the Poverty level in the Coastal Areas of Mukomuko District Using Small Area Estimation: Empirical Best Linear Unbiased Prediction Method

Download28 downloads
  • @INPROCEEDINGS{10.4108/eai.2-8-2019.2290477,
        author={Etis  Sunandi and Dian  Agustina and Herlin  Fransiska},
        title={Estimating the Poverty level in the Coastal Areas of Mukomuko District Using Small Area Estimation: Empirical Best Linear Unbiased Prediction Method},
        proceedings={Proceedings of the 1st International Conference on Statistics and Analytics, ICSA 2019, 2-3 August 2019, Bogor, Indonesia},
        publisher={EAI},
        proceedings_a={ICSA},
        year={2020},
        month={1},
        keywords={coastal area eblup poverty data small area estimation},
        doi={10.4108/eai.2-8-2019.2290477}
    }
    
  • Etis Sunandi
    Dian Agustina
    Herlin Fransiska
    Year: 2020
    Estimating the Poverty level in the Coastal Areas of Mukomuko District Using Small Area Estimation: Empirical Best Linear Unbiased Prediction Method
    ICSA
    EAI
    DOI: 10.4108/eai.2-8-2019.2290477
Etis Sunandi1,*, Dian Agustina1, Herlin Fransiska1
  • 1: Department of Mathematics, Faculty of Mathematics and Natural Sciences, The University of Bengkulu, Bengkulu, 38125, Indonesia
*Contact email: esunandi@unib.ac.id

Abstract

This research aims to estimate the poverty level in the Coastal Areas of Mukomuko District using small area estimation. One of the estimation methods on small area estimation is Empirical Best Linear Unbiased Prediction (EBLUP). using the method, the poverty estimator in the coastal area of Mukomuko District is obtained. The evaluation of parameter estimator is calculated by the value of MSE (Mean Square Error) using Bootstrap resampling method. Based on the result of the study is seen that the MSE value of EBLUP estimators is smaller than the MSE value of the direct estimator in each village. The MSE value of the EBLUP estimators is smaller than the MSE value from the direct estimator for each village. This indicates that the estimation with the EBLUP method can improve the estimation of parameters.