Judul: Kajian Empiris Perbandingan Metode Sampling Dalam Menduga Populasi Minimarket Di Indonesia.
Abstrak: Minimarket merupakan salah satu dari tiga jenis toko modern. Minimarket dapat memberikan kontribusi positif terhadap sektor perdagangan. Namun, keberadaannya juga dapat membuat makin semrawutnya tata kota di suatu wilayah. Selama ini informasi populasi minimarket, hanya berasal dari data yang dikumpulkan 3 kali dalam 10 tahun. Survei secara berkala (3 atau 6 bulan sekali) dapat menjadi solusi untuk menduga populasi seperti berapa jumlahnya dan sejauh mana dampak nya terhadap sektor-sektor ekonomi yang berkaitan. Survei memerlukan sejumlah tahapan. Salah satunya adalah melakukan sampling. Dengan melakukan sampling, parameter populasi yang tidak diketahui dapat diperkirakan berdasarkan nilai-nilai dari unit pengamatan dalam sampel. Tujuan dari penelitian ini adalah untuk mendapatkan metode sampling yang terbaik untuk memperkirakan populasi minimarket di Indonesia. Sumber data untuk simulasi adalah dari PODES 2011, menggunakan data dari desa-desa yang memiliki minimarket. Metode analisis memiliki beberapa langkah. Langkah pertama adalah eksplorasi data minimarket dan langkah kedua adalah estimasi parameter menggunakan 100 kali simulasi di beberapa ukuran sampel yang berbeda. Langkah selanjutnya adalah membandingkan hasil estimasi parameter berdasarkan nilai bias, standard error, dan MSE. Penelitian ini membandingkan estimasi parameter dalam satu metode sampling, dan antara satu metode sampling dengan yang lain. Untuk metode satu tahap sampling, stratified random sampling (menggunakan status pemerintah daerah sebagai strata) pada ukuran sampel 1000 hasil estimasi parameter memiliki akurasi tertinggi. Nilai MSE adalah 3,9 juta. Dan untuk metode sampling dua tahap, stratified two stage cluster sampling pada ukuran sampel 1000 di 15 provinsi (menggunakan status pemerintah daerah sebagai strata) memiliki akurasi tertinggi dengan MSE sebesar 4,3 juta.
Keyword: sampling, perbandingan, simple, stratified, cluster, minimarket

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.
Keyword: 

Judul: Hydroxyapatite-Chitosan Composite Coating on Stainless Steel 316 to Improve Corrosion Resistance
Abstrak: Metals that were used in bone implantation should have good corrosion resistance that were not easily corroded when implanted into the body. Metal corrosion resistance of stainless steel 316 can be enhanced through the metal coating by hydroxyapatite-chitosan composite with composition ratio of hydroxyapatite (gram) and chitosan 3% (mL) 0.2:0, 0.2:0.1, 0.2:0.5, 0.2:1.0, and 0.2:1.5. Besides improving the corrosion resistance of metal, the presence of chitosan also maintain the position of hydroxyapatite on metal surfaces. Corrosion resistance increases with increasing amount of chitosan added and the best composition of hydroxyapatite-chitosan composite was 0.2:1.0.
Keyword: