Judul: Kajian Aktivitas Antioksidan dan Antimikroba Ekstrak  Biji, Kulit Buah , Batang dan Daun Tanaman Jarak Pagar  (Jatropha curcas L.)
Abstrak: Saat ini, jarak pagar (Jatropha curcas L.) menjadi salah satu tanaman penghasil bahan bakar nabati yang cukup pesat perkembangannya. Selain pemanfaatan sebagai bioenergi, jarak pagar juga berpotensi dalam pengembangan produk di bidang pertanian, obat-obatan serta produk perlindungan tubuh. Tanaman jarak mengandung senyawa-senyawa aktif seperti β-sitosterol, stigmasterol, curcin, flavonoid dan 12-deoksil-16-hidroksiforbol (forbol ester). Ekstrak pelarut forbol ester memiliki kemampuan membunuh serangga, fungi, dan moluska sehingga berpotensi sebagai antimikroba. Curcin bersifat antimikroba yang dapat melawan Staphylococcus aureus dan Escherichia coli (Tim Jarak Pagar RNI, 2006). Menurut Hodek et al. (2002), flavonoid yang tekandung dalam ekstrak kulit batang jarak memiliki aktivitas biologi seperti antimikroba, anti alergi dan antioksidan. Kandungan senyawa-senyawa aktif pada tanaman jarak perlu diketahui dengan benar sehingga dapat menjadi dasar pengembangan produk-produk turunan senyawa aktif berbasis jarak pagar. Tujuan dari penelitian ini adalah untuk mengetahui rendemen ekstrak yang terkandung pada berbagai bagian tanaman jarak pagar yang terdiri dari biji, kulit buah, batang dan daun jarak pagar serta untuk mengetahui aktivitas antioksidan dan aktivitas antimikroba dari bagian - bagian tanaman tersebut.
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Judul: Aktivitas Antioksidan dan Antimikroba Fraksi Ekstrak Daun dan Ranting Jarak Pagar ( Jatropha curcas L. ) serta Pemanfaatannya pada Produk Personal Hygien
Abstrak: The development of jarak pagar (Jatropha curcas L) in Indonesia need to be followed by the optimum utilization of all parts of the plants, including the leaves and twigs. Assessment of antioxidant and antimicrobial activity of leaves and twigs extract/extract fraction of Jatropha curcas L and their use in personal hygiene products, is an effort to increase added value of Jatropha curcas’s leaves. Extract of Jatropha curcas in this study were obtained trough a solvent extraction process using ethanol 96% by the method of soxhlet and maceration. Extract fraction obtained by performing advanced stages in the extract called fractination. Antioxidant activity was analized by using DPPH method at concentration of 4, 6, 8, 10, 12, and 20 ppm. While the analysis of antimicrobial activity performes by well diffusion method against Candida albicans, Microsporum gypseum, and Pseudomonas aeruginosa at the concentration of extract/extract fraction 1, 2, and 3%. The result showed that crude extract of maceration and ethyl acetate fraction of soxhlet have the highest antioxidant activity with IC50 values of 7.2 and 7.8 ppm where this values were not significantly different. In other side, the result of antimicrobial activity indicated the present of antimicrobial inhibitory of maceration crude extract against Microsporum gypseum. It proved by the formation of clear zones of inhibition around the wells with diameter of 12, 14, and 20 mm for concentration 1, 2, and 3%. The ethyl acetate fraction showed the inhibitory against Microsporum gypseum only at concentration of 3% extract with diameter of inhibitory zones 14 mm. The extract/extract fraction showed no inhibitory activity against other microbes. Utilization of selected extract fraction applied to one of personal hygiene product, transparent soap, by utilizing its antioxidant activity. Soap with the addition of ethyl acetate fraction of Jatropha curcas at a concentration level of 1.0% produces soap with antioxidant activity of 37.25% and the rate of foam stability about 83.23%.
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Judul: Mixed effect models for high –dimensional longitudinal data with latent variables
Abstrak: A set of data that consist of repeated measurements on a large number of outcomes and covariates are known as high-dimensional longitudinal data. The high-dimensional longitudinal data may consist of several effects of interest that cannot be directly measured, known as latent factors or latent variables. During the last decade, the multivariate responses or high-dimensional in longitudinal data have been a big issue. The analysis of high-dimensional longitudinal data is complicated due to its complex correlation structures between outcomes. To understand changes over time of outcome variables, having correlations in individuals with explanatory variables is not enough. Hence, complex correlation structures between outcomes need to be considered. One approach that is commonly used to overcome high-dimensional longitudinal data is simultaneous equation modeling. A well-known simultaneous equation modeling method is the structural equation model (SEM). This approach has several appealing modeling abilities and can be used for high-dimensional longitudinal data. Under the SEM framework, the continuous time SEM is developed to avoid some issues associated with autoregressive and cross-lagged problems in SEM. Another simultaneous equation modeling method is by combining factor analysis and multivariate analysis methods to overcome high dimensional longitudinal data, namely latent factor linear mixed model (LFLMM). The factor analysis is used to reduce the high-dimensional outcomes, and the multivariate linear mixed model is used to study the longitudinal trends of several latent factors. One example of high-dimensional longitudinal data is the General Election Study. This study is carried out repeatedly to observe tendencies towards political attitudes and behavior over time in Belgium. The data contain political information, knowledge, perceptions, and preferences of a political party and the level of participation in politics. One of the most interesting things to study from the data is to analyze the change of political attitudes and behavior of respondents over time. Also, the relationship of changes in these outcomes is important to analyze. The General Election Study in Belgium was designed to include a representative sample of the target population under the Belgian electorate, so accurate estimates about the population could be made. This sampling design was created by the Institute for Social and Political Opinion (ISPO) and the Inter-university Center for Political Opinion Research (PIOP). The Belgian data set contained three subsamples, the Flemish (Dutch-speaking), the Walloon (French-speaking), and the Brussels Capital Region (Dutch and French-speaking). Several studies conducted on the Belgium data are carried out to understand the relationships between the latent variables Individualism (I), Ethnocentrism (E), and Authoritarianism (A) in Flanders. Cross-sectional or a longitudinal studies have also been carried out. In such cases, it is critical to capture the trend of the latent variables over time and, more importantly, whether there is any association or relationships between the development of nationalism (N), ethnocentrism (E), individualism (I), and authoritarianism (A) in Belgium. An empirical analysis of CT-SEM has been done to present the interdependencies among the four latent variables mentioned above on the basis of the General Election Studies for Belgium in 1991, 1995, and 1999 (Interuniversitair steunpunt politieke-opinieonderzoek, 1991, 1995, 1999). Although the four variables have been the subject of
Keyword: Belgium, CT-SEM, high-dimensional longitudinal data, LFLMM, Supplemented EM Algorithm