Judul: Keragaan usaha budidaya ikan hias anggota kelompok nusa hias desa Cibitung Tengah, kecamatan Tenjolaya kabupaten Bogor
Abstrak: Kelompok Pembudidaya Ikan Hias Nusa Hias merupakan kelompok pembudidaya yang berprestasi di Kabupaten Bogor. KEgiatan usaha budidaya ikan hias yang dilakukan Kelompok Pembudidaya Ikan Hias Nusa Hias bersifat tradisional, namun belum dapat dinyatakan kegiatan usaha mana yang berpeluang untuk dikembangkan, karena belum adanya perhitungan analisis usaha dan kelayakan yang dilakukan terhadap kegiatan usaha kelompok ini.
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Judul: Strategi Bisnis Ikan Hias Air Tawar Pada Kelompok Pembudidaya Ikan Hias Nusa Hias, Desa Cibitung Tengah Kecamatan Tenjolaya Kabupaten Bogor
Abstrak: Nusa Hias adalah salah satu kelompok pembudidaya ikan hias, tanaman hias dan ikan konsumsi yang berada di Kabupaten Bogor. Usaha bisnis yang dijalankan tidak lepas dari berbagai masalah yang berada di dalam maupun di luar kelompok dalam memformulasikan, mengimplementasikan dan mengevaluasi strategi agar tujuan dan sasaran dapat tercapai. Strategi bisnis yang diterapkan pada KPIH Nusa Hias bertujuan untuk menganalisis faktor internal berupa kekuatan dan kelemahan dan faktor eksternal berupa peluang dan ancaman KPIH Nusa Hias. Manfaat penelitian bagi KPIH Nusa Hias sebagai bahan pertimbangan dalam membuat kebijakan dan strategiKPIH Nusa Hias. Metode penelitian yang digunakan adalah studi kasus dengan satuan kasus KPIH Nusa Hias, sumber data diperoleh dari data primer dan data sekunder, pengambilan responden menggunakan purposive sampling dan analisis data menggunakan IFE, EFE, IE, SWOT, SPACE, GS dan QSPM. Berdasarkan analisis matriks IFE diperoleh skor sebesar 2,739 dan matriks EFE diperoleh skor sebesar 2,618 dengan rata-rata 2,678. Hal ini menunjukkan bahwa KPIH Nusa Hias mampu memanfaatkan kekuatan internal kelompok untuk memperoleh peluang eksternal yang lebih besar serta mengatasi kelemahan dan menghindari ancaman yang dapat membahayakan usaha ikan hias. Selanjutnya dilakukan analisis strategi IE, SWOT, SPACE dan GS. Langkah terakhir adalah melakukan analisis penentuan prioritas alternatif strategiterbaik pengembangan pasar, penetrasi pasar dan pengembangan produk. Pengembangan pasar dilakukan melalui kemitraan,promosi dan peningkatan fasilitas. Penetrasi pasar dilakukan melalui temu usaha dengan para pembudidaya, suplayer, pemerintah pihak swasta, pemerintah, pihak swasta dan perusahaan ekspor ikan hias. Sedangkan pengembangan produk dilakukan dengan menambah jumlah, ukuran dan jenis ikan hias yang dibudidayakan.
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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