Judul: Seleksi dan Formulasi Konsorsium Bakteri untuk Mengendalikan Penyakit Blas (Pyricularia oryzae) pada Tanaman Padi
Abstrak: Penyakit blas yang disebabkan cendawan Pyricularia oryzae merupakan salah satu hambatan pada produksi padi lahan kering maupun lahan basah. Penelitian ini dilakukan untuk mencari agen pengendali hayati (konsorsium bakteri) untuk mengendalikan penyakit blas. Metode pertama yang dilakukan yaitu uji kompatibilitas in vitro bakteri Bacillus firmus E65, Serratia marcescens E31, Pseudomonas aeruginosa C32b, Bacillus cereus II.14, serta kombinasi konsorsiumnya terhadap cendawan P. oryzae. Hasil uji menunjukkan 2 perlakuan yaitu A2 yang menggunakan isolat E65 dan perlakuan A6 yang menggunakan konsorsium E65, II.14, dan C32b memiliki luas daerah penghambatan terhadap P oryzae terbaik dengan persentase penghambatan 73-85% dan sebesar 66-83%. Pembuatan formulasi dilakukan untuk dua perlakuan terbaik dengan bahan pembawa talk, bentonit, minyak, dan kaldu nutrien (suspensi). Hasil aplikasi in vivo menunjukkan formulasi suspensi memiliki potensi penekanan blas paling baik.
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Judul: Pengujian Formulasi Konsorsium Bakteri terhadap Penyakit Blas Leher (Neck Blast ) pada Tanaman Padi
Abstrak: Pemanfaatan bakteri sebagai bentuk pengendalian hayati dalam mengurangi serangan penyakit padi perlu dilakukan. Penelitian ini bertujuan untuk mengetahui keefektifan formula konsorsium bakteri sebagai pengendali penyakit blas leher (Neck Blast) pada tanaman padi. Perlakuan formula isolat yang digunakan masing-masing adalah A2 (B. firmus E65), A6 (B. firmus E6 + P. aeruginosa C32b + B. cereus II.14), A8 (B. firmus E6 + P. aeruginosa C32b + B. cereus II.14+S. marcescens E31) serta penambahan bahan agensia yang diberikan pada masing-masing kode perlakuan. Formula bahan agensia yang digunakan berupa talk (T), bentonit (B), dan pupuk organik granula (P). Pengujian secara in vitro dari konsorsium suspensi A6 dan A8 serta formula dengan bahan agensia (AST, dan A8P) dapat menghambat pertumbuhan P. oryzae masing-masing sebesar 46,29%, 54,45%, 40,00%, 42,59%. Hasil uji efektivitas formulasi terhadap intensitas serangan blas leher menunjukkan intensitas serangan terkecil yaitu ISA8 (13,89%), IPA6 (13,44%), dan ITA6 (14,59%). Selain itu pemberian formula memberikan pengaruh tehadap jumlah anakan total, jumlah malai setelah 94 hari tanaman (hst) yaitu dengan pemberian formula IPA6 sebesar 25 untuk jumlah anakan total dan 12,3 untuk jumlah malai. Pemberian formulasi juga berpengaruh nyata terhadap bobot basah dan bobot kering tanaman. Hasil tersebut menunjukkan bahwa penyemprotan dengan formula IPA6, ITA6 dan ISA8 pada tanaman padi memberikan pengaruh penghambatan terhadap penyakit blas leher. Pemberian formula IPA6 memberikan pengaruh terhadap jumlah anakan total dan jumlah malai serta berpengaruh nyata terhadap berat biomassa tanaman padi Inpari 13.
Keyword: Neck Blast, Pyricularia oryzae, Bacterial Consortium, Biological Control

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