Judul: Penggunaan zat antimikroba untuk penanggulangan mastitis
Abstrak: Fenyebab utama mastitis adalah mikroba, oleh sebab i tu untuk penanggulangannya dipergunakan zat antimikroba. Sumber infeksi pada kejadian mastitis pada sapi perah terutama adalah lingkungan. maka didalam penanggula- ngannya selain dilakuka, pengobatan pada sapi penderita juga sumber infeksi pada lingkungan harus dimusnahkan. Pengobatan mastitis pada sapi perah dapat dipakaian tibiotika dan kemoterapetika. Penicillin dan Streptomycin saat ini kurang efektif untuk pengobatan mastitis, tetapi campuran Ampicillin dan Uloxacillin memperlihatkan daya kerja yang lebih baik. Untuk membasmi sumber infeksi di lingkungan dapat di pergunakan disinfektan dan sanitizer. Disinfektan yang biasa digunakan di perusahaan susu ndalah Nahypochlorit, sedangkan sanitizer yang cukup baik adalah waOH 4%. Untuk mengetahui antimikroba mana yang efektif dalam pengobatan mastitis maka uji kepekaan antimikroba terha dap bakteri-bakteri penyebab mastitis akan sangat membantu. Teknik tentang cara penentuan antibiogram suatu anti mikroba dapat ditempuh dengan cara pengenceran, cara cakram dan cara penipisa: Cara cakram adalah cara yang mudah dan sering dilakukan di laboratoium. ...
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Judul: Uji Sensitivitas Antibiotik Beberapa Bakteri Penyebab Mastitis.
Abstrak: Salah satu kesuksesan pengobatan mastitis pada sapi perah yaitu melalui penggunaan antibiotik secara tepat. Penggunaan antibiotik secara tidak rasional dan tidak sesuai prosedur menyebabkan terjadinya resistensi antibiotik. Tujuan penelitian ini adalah menguji sensitivitas beberapa bakteri yang diisolasi dari susu sapi yang menderita mastitis klinis terhadap berbagai antibiotik. Bakteri-bakteri yang terisolasi dan teridentifikasi yaitu Yersinia sp., Escherichia coli, Pseudomonas sp., Pseudomonas diminuta, Enterobacter aerogenes, Alcaligenes sp., Serratia sp., Staphylococcus aureus, S. epidermidis, dan Bacillus sp.. Bakteri S. aureus, Pseudomonas sp., E. aerogenes, dan E. coli diuji sensitivitasnya terhadap antibiotik ampisilin, karbenisilin, sefalotin, eritromisin, gentamisin, tetrasiklin, dan trimetoprim dengan metode disk diffusion test Kirby-Bauer. Berdasarkan hasil uji sensitivitas, semua bakteri yang diuji telah menjadi bakteri yang multiresisten. Escherichia coli resisten terhadap semua antibiotik yang diuji; S. aureus dan E. aerogenes masih sensitif terhadap gentamisin, tetrasiklin, dan trimetoprim; sedangkan Pseudomonas sp. hanya sensitif terhadap gentamisin.
Keyword: bakteri, mastitis, resistensi antibiotik

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