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  The Estimation of The Total Number of Agricultural Families in Ogan Komering Ilir Regency of South Sumatra Province Under Incomplete Sampling Frame  
  Authors : Asih Maulida, Farit Mochamad Afendi , Kusman Sadik
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The various geographic and topography condition in Indonesia makes several areas in Indonesia have limited access. It needs a high cost and spends a long time on collecting data onto this area so some researchers tend to exclude this area from the sampling frame. Incomplete sampling frames influence the inclusion probabilities of the non-included unit in sampling frame and arises bias. Several approaches could be used to reduce bias, one of them is Predecessor-Successor method. We used a direct estimation of the total number of agricultural families in Ogan Komering Ilir regency by classical sampling theory and PredecessorSuccessor method then evaluated their estimators. The results showed Predecessor-Successor method could reduce bias more effectively than classical sampling theory on a large sample size. Using an appropriate estimation method of a complete frame, the best estimator will be gotten. If it is unattainable, Predecessor-Successor method can be used to direct estimates of population quantity.


Published In : IJCSN Journal Volume 6, Issue 6

Date of Publication : December 2017

Pages : 792-799

Figures :02

Tables : 03


Asih Maulida : Student of masters degree programs in applied statistics at Bogor Agricultural University, Indonesia and attained bachelor degree from the Gajahmada University in 2006.

Farit Mochamad Afendi : Lecturer of Department of Statistics, Bogor Agricultural University, Indonesia. His research interest in Geoinformatics. His doctorate degree was attained from Nara Institute of Science and Technology, Japan.

Kusman Sadik : Lecturer of Department of Statistics, Bogor Agricultural University, Indonesia. His research interest in statistical modelling, small area estimation, robust statistics. His doctorate degree was attained from Bogor Agricultural University, Indonesia. A part of his courses and research of doctoral was taken at the University of Maryland, United States.


Coverage Error, Predecessor-Successor, Remote Area

A biased value of the estimator which is caused coverage error due to the incomplete sampling frame will be significantly minimized by the Predecessor-Successor method on medium and large sample size. On the other hand, classical sampling theories include either simple sampling method or stratified sampling method will be more efficient than the Predecessor-Successor method for small and rather medium sample size. Using the appropriate estimation method can minimize the biased problems. The results of the estimator would be better if all of the units were the target of the population and included in a frame. However, if a complete frame cannot be obtained especially region, which has remote area, Predecessor-Successor method can be chosen as an alternative method to estimate a population quantity.


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