Judul: Determining Optimum Strata Boundary Points on Stratified Random Sampling using Dynamic Programming (Case: Expenditure per Capita of East Java Province Year 2008)
Abstrak: 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. For the two strata to get the optimal point on the boundary x1 = 0.002. For the formation of three strata obtained the optimal point on the boundary x1 = -0.546 and x2 = 0.552. For the formation of four strata obtained optimal boundary point is x1 = -0.869, x2 = 0.003 and x3 = 0.878. In forming five strata obtained optimal boundary point x1 = -1.096, x2 = -0.331, x3 = 0.339 and x4 = 1.107. The establishment of a total of six strata obtained the optimal point on the boundary x1 = -1.267, x2 = -0.569, x3 = 0.005, x4 = 0.579 and x5 = 1.281.
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Judul: Modified local getis statistic on AMOEBA weights matrix for spatial panel model and its performance
Abstrak: Classical regression model assumes that no interaction between objects. However, in some cases these conditions are not hold so we have to find an alternative solution that can accommodate the interaction effect. Spatial model is a model that can accommodate the interaction effect by adding a spatial component in the right hand side that represented by a spatial weights matrix. Generally, spatial weighted matrix uses closeness concept among the units, without include the proximity of interest variables. Another way to construct a spatial weights matrix is to use AMOEBA procedure introduced by Aldstadt and Getis. In this procedure, each element of the matrix, beside is determined by the closeness relationship, also determined by proximity among variables using local Getis statistics. Getis and Ord have claimed that the statistic is normally distributed. However, empirically, normal curve test shows that normality of local Getis statistic is influenced by variable of interest (original variable). Due to this reason, we propose a modification of local Getis statistic, namely Gnew, which gives a robust result. A modification of local Getis statistics by transforming to ( ) gives a robust result, that is, it has normal distribution for any distribution of Xj. To assess local Getis and modified local Getis statistics, they are applied on AMOEBA procedure to create weights matrix, namely WG and WGnew. We compare them with contiguity matrix (WC). The model that used for comparison is spatial dynamic panel model with respect to Cizek. By using simulated data and root mean square error relative criteria, it is found that WGnew gives the best performance. In the next stage, we evaluate spatial matrix performance in model to real data, whereas in this case, we take poverty issue in Center Java Province. Poverty is one of the issues of concern at both the central and local government. Central Java was the province with the second largest number of poor people in Indonesia. There are many factors that influence poverty, some of them are GDP per capita, population, education, share of agriculture labor, share of industry labor, share of trading labor and share of services labor (four dominant sectors). Focus of this research is to study influence of labor of junior high school graduates, population, GDP per capita and the share of labor in four dominant sectors to the number of poor people using spatial panel model. Sources of data for modeling obtained from central BPS and Center Java BPS from 2008 to 2012. The research results show that an increase in population, labor of junior high school graduates and share of agricultural labor can increase the number of poor people. Meanwhile the increase in labor share of industry, trade and service sectors and GDP per capita can decrease the number of poor people. Based on these findings, there are several ways to reduce the number of poor people, such as to control population by family planning program (KB program), improving quality of human resources, expand some business, especially in sectors of industry, trading and services.
Keyword: poverty, PDB per capita, random permutation, local Getis statistic, modified local Getis statistic

Judul: Karakterisasi molekuler virus gemini asal tanaman tomat
Abstrak: Virus gemini merupakan salah satu kelompok patogen utama yang menyerang dan menimbulkan kerusakan yang besar pada tanaman sayuran di daerah tropik dan sub tropik. Pada umumnya kerugian yang ditimbulkan oleh adanya suatu epidemi berkisar antara 30%-100%. Gejala tanaman tomat yang terinfeksi oleh virus gemini kadangkala mirip dengan gejala yang disebabkan oleh infeksi virus yang lain khususnya Potyviridae dan Tobamoviridae. Dengan demikian, gejala penyakit saja tidak cukup untuk digunakan dalam mengidentifikasi virus gemini. Pengetahuan tentang karakter molekuler virus gemini pada tanaman tomat yang bergejala menjadi sangat penting dalam mengidentifikasi virus gemini tersebut. Penelitian ini bertujuan untuk mengamati gejala luar, melakukan purifikasi dan mempelajari beberapa karakter molekuler virus gemini asal tanaman virus tomat. Karakter molekuler yang dipelajari meliputi ukuran dan jenis asam nukleat serta ukuran protein. Deteksi virus dengan metode polymerase chain reaction (PCR) dilakukan untuk memperkuat hasil analisis karakter molekuler. Isolat virus gemini asal tanaman tomat yang diperoleh dari Bandung, Jawa Barat ditularkan dengan serangga vektor B. tanaman tomat. daerah tabaci dari dan ke Gejala yang ditimbulkannya berupa penebalan tulang daun permukaan bawah, daun menggulung ke atas atau ke bawah, berkeriput dan tepi daun mengalami klorosis. Virus gemini isolat Bandung ini berhasil dimurnikan dari daun tomat yang bergejala dengan menggunakan metode yang digunakan ..dst
Keyword: virus gemini, tanaman tomat, purifikasi virus, isolasi tanaman