PENENTUAN TITIK-TITIK BATAS OPTIMUM STRATA PADA PENARIKAN CONTOH ACAK BERLAPIS DENGAN PEMROGRAMAN DINAMIK (Kasus : Pengeluaran per Kapita Propinsi Jawa Timur Tahun 2008)

Mahyudi Mahyudi

Abstract


Optimum stratification is the method of choosing the best boundaries that make strata internally homogeneous, given some sample allocation. In order to make the strata internally homogenous, the strata should be constructed in such a way that the strata variances for the characteristic under study be as small as possible. This could be achieved effectively by having the distribution of the main study variable known and create strata by cutting the range of the distribution at suitable points. The problem of finding Optimum Strata Boundaries (OSB) is considered as the problem of determining Optimum Strata Widths (OSW). The problem is formulated as a Mathematical Programming Problem (MPP), which minimizes the variance of the estimated population parameter under Neyman allocation subject to the restriction that sum of the widths of all the strata is equal to the total range of the distribution. The distributions of the study variable are considered as continuous with standard normal density functions. The formulated MPPs, which turn out to be multistage decision problems, can then be solved using dynamic programming technique proposed by Bühler and Deutler (1975). After the counting process using C++ program received the width of each stratum. From these results the optimal boundary point can be determined for each stratum. 

Keywords


Stratified Random Sampling; Optimum Stratification; Standard Normal Distribution; Mathematical Programming; Dynamic Programming

References


Aoyama H. 1954. A Study of Stratified Random Sampling. Annals of The Institute of Statistical Mathematics 6:1-36.

Bühler W and Deutler T. 1975. Optimal Stratification and Grouping by Dynamic Programming. Metrika 22:161-175.

BPS [Badan Pusat Statistik] Provinsi Jawa Timur. 2008. Pendataan Potensi Desa 2008 Propinsi Jawa Timur . Jawa timur: Badan pusat Statistik.

Baillargeon S and Rivest LP. 2010. Univariate Stratification of Survey Populations with The Package Stratification. Paper in Progress.

Cochran WG. 1977. Sampling Techniques, 3rd Edition. New York: John Willey & Sons.

Khan EA, Khan MGM, Ahsan MJ. 2002. Optimum Stratification: A Mathematical Programming Approach. Culcutta Statistical Association Bulletin 52 (special):205-208.

Khan MGM, Najmussehar, Ahsan MJ. 2005. Optimum Stratification for Exponential Study Variable Under Neyman Allocation. Journal of Indian Society of Agriculture Statistics 59(2):146-150.

Khan MGM, Niraj Nand, Nesar Ahmad. 2008. Determining The Optimum Strata Boundary Points Using Dynamic Programming. Survey Methodology 34: 205-214.

Kish L. 1965. Survey Sampling.New York: John Willey & Sons.

Kozak M. 2004. Optimal Stratification Using Random Search Method in Agricultural Surveys. Statistics in Transition 6(5):797-806.

Lavallée P. 1988. Two-way Optimal Stratification using Dynamic Programming. Procedings of The Section on Survey Research Methods; Virginia:646-651.

Lavallée P, Hidiroglou M. 1988. On The stratification of Skewed populations. Survey Methodology 14:33-43.

Levy, Paul S, Stanley L. 1995. Sampling of Populations Methods and Applications Third Edition.New York: John Willey & Sons.

Nicolini G. 2001. A Method to Define Strata Boundaries. Departmental Working Papers 2001-01. Department of Economics, University of Milan, Italy.

Rivest LP. 2002. A Generalization of Lavallée and Hidiroglou Algorithm for Stratification in Business Survey. Survey Methodology 28:191-198.

Siagian P.2006. Penelitian Operasional: Teori dan Praktek. UI-PRESS.




DOI: http://dx.doi.org/10.24042/ajpm.v6i1.60

Refbacks

  • There are currently no refbacks.


 

Creative Commons License
Al-Jabar : Jurnal Pendidikan Matematika is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.