Judul: Gini Ratio and the Components Prediction based on YbarraLohr Model with Estimated Sampling Variance
Abstrak: Gini ratio is one of the parameters used to measure income inequality, so it is necessary to know the value of the Gini ratio down to the level of smaller areas such as subdistricts. The Gini ratio classification is divided into three, those are very high (0,50 – 0,70), moderate (0,36 -0,49), and low (0,20 – 0,35). The components of the Gini ratio according to BPS for the subdistrict level are the average expenditure per capita and the relative frequency of households for each expenditure class in the subdistrict. Per capita expenditure data available through SUSENAS is designed to obtain national statistics down to the district level, so it is necessary to make estimates for the subdistrict expenditure class level. Direct estimation for small samples can cause large standard errors, therefore small area estimation with Logarithmic Transformation is used as a solution to fulfill the linearity assumption of the model to estimate the average per capita expenditure for each expenditure class for each subdistrict in Depok City in 2020. The expenditure class in this study was determined based on the BPS expenditure class and the distribution of response variable data. The Ybarra-Lohr model at the area level is used due to the availability of accompanying variables at the area level that contain errors which are also available in SUSENAS data. The area is the expenditure class in each subdistrict in Depok City. Estimation was also carried out in one sampleless area in one subdistrict. The sampling variance needed to estimate the average per capita expenditure, is estimated by comparing several methods of estimation, including direct estimation, probability distribution, and bootstrap repetitions of 1000, 10000 and 50000. Estimation of sampling variance and small area estimation analysis using the Ybarra-lohr model and logarithmic transformation done using R software with the help of the saeme package. The method of estimating the model variance with the probability distribution yields an estimate of the average expenditure per capita with the smallest RRMSE, and the random effect variance and the goodness of the YbarraLohr model are σ̂v 2 = 0.686, R 2= 0.929. The results of estimating the best average per capita expenditure for each expenditure class are used to obtain the gini ratio for each subdistrict in Depok City in 2020. Classification is based on the level of inequality, gini ratio with indirect results in all subdistricts in Depok City which are included in the low category are Bojongsari, Pancoran Mas, Cipayung, Sukmajaya, Cilodong, Tapos, Beji, and Limo subdistricts. The subdistricts included in the category of moderate inequality are Sawangan, Cimanggis, and Cinere subdistricts.
Keyword: EBLUP log transform, gini ratio, saeme, sampling variance

Judul: Aplikasi Metode Molina dan Rao pada Pendugaan Ukuran Kemiskinan Moneter di Kabupaten dan Kota Malang
Abstrak: The strategy of poverty solution needs the availability of accurate data regarding the poverty itself. One of the most important things on the poverty data is the poverty measurement. The poverty measurement is assumed to become a powerful instrument for the policy makers to focus their attention toward the living condition of poor people. The concept of poverty which is used by Badan Pusat Statistik (The Statistic Center) is the monetary approach by measuring the poverty based on the expenses per capita of the house holders. The indicators used by the BPS in measuring the poverty are the monetary approach developed by Foster, et. al. they are (1) the percentage of poor people [Head Count Index (HCI), P0], (2) Poverty Gap Index [(PGI), P1], and (3) the Distributional Sensitive Index [(DSI), P2]. The estimation calculation of the monetary poverty measurement is done directly by BPS which is based on the data of Survei Sosial Ekonomi Nasional (Susenas)/The National Survey of Socio Economy. This direct estimation method was not be able to give the good accurateness if it is conducted on the small scale sample, therefore the statistical result gained through this method will show the big various score as well as the lack of accuracy. Nevertheless, this situation can be solved by a method called the small area estimation method. This study aims to analyze the sample size on the monetary poverty estimation which is used by BPS and to find the alternative solution on the monetary poverty measurement estimation in the case small sample area. The approach of the study is divided into two groups – the simulation and the application. The simulation was conducted through nine scenarios based on the pattern of which has the combined parameter to make the same expectation score E(). It was also conducted through resampling data by using various size of sample, for 500 repetition. The application in this study is from two data sources, they are the data from the Survei Sosial Ekonomi Nasional (Susenas) in 2008 and the data from the Potensi Desa (PODES)/the village potency in 2008 in East Java. From Susenas data, there are two variables – the data of householders’ expenses per capita as the treatment variable (), and the data of village amount which has kelurahan status as the control variable for the householder member sample (The PODES is used as the source for supporting i.e the proportion of kelurahan status in each kecamatan. This data is used as the control variable for non-sample householder. The result on the simulation approach shows that if the sample size is small, so the estimation value resulted on the direct estimation method is unbiased with big variance. This situation is proved by the simulation comparison of all samples’ size and also by looking into the index bias behavior of bias Relative Bias (RB), Absolute Relative Bias (ARB), and Relative Mean Square Error (RMSE). Whereas, the result from the Bayes empiric found non-zero result. Therefore, the direct estimation can be corrected by the Bayes empiric estimation in term of small scale sample.
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Judul: Embriogenesis ikan buta (Astyanax fasciatus)
Abstrak: Ikan buta Astyanax fasciatus adalah spesies ikan unik dari famili Characidae yang menempati perairan dalam gua di Wilayah La Cueva Chica-San Luis Potasi-Mexico. Ikan ini memiliki mata yang tereduksi (Blind Cavefish) dan warna kulit merah muda, pucat serta mengkilap.
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