Judul: Potensi Bakteri Rizosfer Tanaman Buah Naga sebagai Agens Antagonis Cendawan Neoscytalidium dimidiatum Penyebab Penyakit Kanker Batang.
Abstrak: Buah naga merupakan salah satu tanaman dalam famili Cactaceae yang memiliki prospek baik dalam menunjang kegiatan agribisnis. Salah satu kendala utama dalam budi daya tanaman buah naga adalah penyakit kanker batang yang disebabkan cendawan Neoscytalidium dimidiatum. Gejala penyakit antara lain timbulnya bintik putih yang berkembang menutupi permukaan batang dengan warna kuning cokelat sampai hitam, permukaan batang kasar, tunas mengering dan tanaman mati. Oleh karena itu, diperlukan manajemen penyakit yang baik agar tanaman dapat menghasilkan buah dengan kuantitas dan kualitas yang optimal. Salah satu pengendalian yang menjanjikan adalah aplikasi agens biokontrol yang diisolasi dari rizosfer. Penelitian dilakukan dalam 3 tahap: (1) mengisolasi bakteri rizosfer tanah tanaman buah naga, (2) pengujian in vitro keefektifan bakteri rizosfer terhadap cendawan N. dimidiatum, dan (3) mengidentifikasi bakteri dengan sifat antagonis terbaik. Sebanyak enam isolat dari 120 bakteri terpilih memiliki potensi tinggi sebagai agens biokontrol berdasarkan kemampuannya dalam menghambat N. dimidiatum secara in vitro. Dua isolat dengan daya hambat tertinggi adalah D01 dan P30 dengan daya hambat 41,82% dan 34,83%. Analisis filogenik berdasarkan sekuens gen 16S rRNA menunjukkan bahwa kedua isolat tersebut berturut-turut teridentifikasi sebagai Streptomyces sp. strain BGP65 dan Bacillus paralicheniformis strain NG-ABK-31.
Keyword: Bacillus paralicheniformis, biological control agents, Cactacecae, Hylocereus spp., Streptomyces sp

Judul: Insidensi Penyakit yang Disebabkan Cendawan pada Tanaman Buah Naga Merah (Hylocereus polyrhizus) di Kecamatan Cijeruk dan Leuwiliang Kabupaten Bogor
Abstrak: Tanaman buah naga (Hylocereus sp.) merupakan komoditas hortikultura yang banyak ditanam di Indonesia seiring dengan permintaan pasar yang meningkat. Penyakit tanaman cukup penting dalam usaha tani tanaman buah naga dan sebagian besar disebabkan oleh cendawan. Suatu bentuk usaha pengendalian dapat dilakukan dengan mempelajari insidensi penyakit serta cendawan patogen yang menginfeksi tanaman buah naga merah. Penelitian ini bertujuan mengamati insidensi penyakit dan identifikasi cendawan penyebab penyakit pada tanaman buah naga merah (H. polyrhizus) di sentra pertanaman buah naga Desa Tanjungsari, Kecamatan Cijeruk dan Desa Purasari, Kecamatan Leuwiliang, Kabupaten Bogor. Cendawan patogen pada tanaman buah naga merah di Kecamatan Cijeruk dan Kecamatan Leuwiliang adalah Fusarium sp. (1), Fusarium sp. (2), Gliocladium sp. (1), Gliocladium sp. (2), Colletotrichum sp., Neoscytalidium sp., Alternaria sp. dan empat isolat cendawan patogen belum teridentifikasi. Penyakit pada tanaman buah naga di Kecamatan Cijeruk dan Leuwiliang adalah kanker sulur (Alternaria sp., Neoscytalidium sp.), antraknosa (Colletotrichum sp.), busuk coklat (Fusarium sp.), nekrosis sulur, dan bercak buah. Kanker sulur, nekrosis sulur, dan antraknosa merupakan penyakit utama tanaman buah naga di Kecamatan Cijeruk dan Leuwiliang. Tingkat insidensi dan keparahan penyakit di kedua lahan dipengaruhi oleh pola tanam, pengendalian penyakit, keberadaan gulma, dan iklim mikro
Keyword: kanker sulur, keparahan penyakit, Neoscytalidium sp., patogen

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