ACCURACY COMPARISON OF SIMPLE, SYSTEMATIC, AND STRATIFIED RANDOM SAMPLING FOR ESTIMATING POPULATION (MINIMARKET CASE IN INDONESIA)

This paper aims to compare the accuracy of three methods of sampling, namely Simple Random Sampling (SRS), Systematic Random Sampling and Stratified Random Sampling. The data used as the simulation is data PODES 2011. So the data that is used as a parameter in this study are primary data in the form of data results PODES 2011 were rural / village with minimarket (RVM). The method of analysis is done in two stages. The first phase saw the condition of the minimarket population data as a basis for exploration. The second stage of the estimation simulate the total population and the variance by using simple random sampling, systematic random sampling, and stratified random sampling. The next stage of comparing the results of estimation of population parameters of the sampling methods to the total population of the minimarket PODES 2011. The results are reviewed based on the accuracy of each method. Stratified random sampling method (DKM as a base coating) with a sample size of 500 generate predicted values with the highest degree of accuracy compared with the SRS and systematic random sampling. Its bias value at 22 outlets, its standard error of 2606.2 outlets, and his MSE of 6.79254 million. Keywords: accuracy, comparison, simple, systematic, stratified, random