Judul: Parameter Estimation Of Correlated Outcome And Covariates Measured With Error In Logistic Regression
Abstrak: In epidemiological studies, it is common to have binary data as the response variable. Hence, the common model applied to represent the relationship between the binary outcome and risk factors is logistic regression. Problems that commonly occur in binary data are intra-class correlation in the outcome variable and measurement error or misclassification in the covariates/risk factors. An alternative statistical procedures, William's procedure and Generalized Estimating Equation for correlated outcome and direct adjustment for measurement error, are used to handle these problems. The application of these methods is implemented to the Children Nutrient Status Data. The data is obtained from the study conducted in June 2000 - October 2000, involving 402 children under five years old in three locations in Central Java. In the analysis of intra-enumerator data, there is an indication of the presence of intra-correlation between data co llected and enumerator.
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Judul: Statistical Analysis for Non-Normal and Correlated Outcome in Panel Data
Abstrak: There are many cases that cannot fulfill some assumptions in statistical analysis, such as normality and independence. In many practical problems, the normality as well independent assumption is not reasonable. For example, data that repeated over time tend to be correlated. If analysis ignores the non independent outcome the Standard Error (SE) on the parameter estimates tends to be too small. Generalized Linear Model (GLM), Generalized Estimating Equation (GEE), and Generalized Linear Mixed Model (GLMM) can be used for nonnormal data using the link functions. GEE includes working correlation matrix to accommodate the correlation in the data. GLMM may overcome the repeated observation and allows individual have different baseline/intercept. The study is aim at comparing result based on those approaches. The data that are used in this study are from BPS and the outcome that are used is poverty proportion. Based on the study shows that GEE approach is better than GLM for marginal model, and GLMM approach is better than GEE with dummy variable.
Keyword: Bogor Agricultural University (IPB), non-normal, GLMM, GLM, GEE, correlation outcome

Judul: Penggunaan Pewarna Alami untuk Modifikasi Permukaan TiO2 sebagai Pemeka Cahaya pada Dye Sensitized Solar Cell
Abstrak: Teknologi yang umum digunakan untuk memanfaatkan energi matahari ialah sel surya. Berdasarkan bahan pembuatannya, sel surya dapat dibedakan menjadi tiga macam, yaitu sel surya silikon, sel surya lapis tipis, dan sel surya organik atau dye sensitized solar cell (DSSC). DSSC terdiri atas elektrode kerja, pewarna, elektrolit, dan elektrode lawan. Elektrode kerja merupakan kaca oksida indium timah yang dilapisi semikonduktor pada bagian konduktifnya. Pewarna sangat penting dalam DSSC karena berperan sebagai bahan pemeka cahaya. Pewarna alami banyak dikembangkan untuk DSSC karena ketersediaan yang melimpah di alam. Bunga tapak dara mengandung senyawa antosianin sehingga dapat digunakan sebagai pewarna alami pada DSSC. Interaksi antara antosianin dan TiO2 sebagai semikonduktor dianalisis dengan studi pustaka. Hasil yang ditunjukkan ialah antosianin memiliki interaksi yang baik dengan TiO2 berdasarkan beberapa karakterisasi sehingga bunga tapak dara berpotensi menjadi bahan pemeka cahaya.
Keyword: antosianin, DSSC, pemeka cahaya, TiO2