Judul: Masalah Reproduksi Pada Sapi Perah di Daerah Tingkat II Cirebon
Abstrak: Sapi perah cukup penting artinya bagi peternak sehingga dijuluki "Raja Kaya" dan merupakan tiga sumber "Tambang Emas" (pu tih-susu, merah-daging dan hijau-pupuk). "Tambang Emas Putih" telah dirasakan manfaatnya dalam mensejahterakan masyarakat. Usaha peternakan sapi perah di Daerah Tingkat II Cirebon umumnya bersifat peternakan rakyat dengan pemilikan rata- rata 4 - 8 ekor sapi. Beternak sapi perah merupakan mata pencaharian tambahan dengan cara beternak yang dilalukan secara intensif.
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Judul: Penampilan Reproduksi Sapi Perah Di Kabupaten D.T.II Cirebon
Abstrak: Tujuan studi kasus ini adalah untuk mengetahui penampilan reproduksi sapi perah di Kabupaten Daerah Tingkat II Cirebon. Sapi yang digunakan sebagai bahan studi kasus ini adalah sapi perah milik peternak (rakyat) di Kecamatan Sumber, Weru, Cirebon Barat, Astanajapura, Babakan, Ciledug dan Kecamatan Waled. Populasi ternak sapi perah di Kabupaten Cirebon selalu mengalami penurunan jumlahnya tiap tahun. Jumlah populasi sekarang tinggal sepertiga dari jumlah sapi perah bantuan pemerintah yang telah disampaikan pada masyarakat, baik melalui kredit koperasi maupun yang melalui dinas peternakan. Pola beternak masyarakat pada umumnya masih bersifat tradisional, tatalaksana peternakan belum terlaksana dengan baik dan benar. Tehnologi yang dimanfaatkan masih sederhana, baik dalam menangani kesehatan ternak, pemberian pakan, penanganan reproduksi, maupun penanganan dan pengelolaan produksi ternaknya. Tingkat pendidikan peternak masih rendah, dan bukan merupakan pendidikan kejuruan yang berhubungan dengan bidang peternakan. Pengetahuan beternak lebih banyak dipero- leh dari pengalaman pribadi, dari leluhur secara turun temurun, maupun dari penyuluhan dan kursus-kursus pertanian atau peternakan dari dinas peternakan. Usaha peternakan sapi perah di Kabupaten Cirebon pada umumnya bukan merupa- kan usaha (pekerjaan) utama bagi peternak. Ternak umumnya dikandangkan sepanjang hari, sedikit sekali peternak yang mau melepas ternaknya untuk memberi kesempatan bergerak (latihan). Pemberian pakan umumnya dua kali sehari, dengan hijauan yang cukup, tetapi sedikit sekali peternak yang menambahkan konsentrat sebagai makanan tambahan atau makanan penguat. Ternak sapi perah di Kabupaten Cirebon, hampir semuanya dikawinkan dengan inseminasi buatan (IB). Tingkat kesuburan ternak sapi perah di Kabupaten Cirebon masih rendah. Tingkat efisiensi reproduksinya juga rendah, service per conceptionnya mencapai 2,4, conception rate hanya men- capai 50,29% dan calving intervalnya rata-rata mencapai 14- 16 bulan, sedangkan angka kelahiran seluruhnya hanya menca- pai 43,2%...
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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