Judul: Analisis Logistik Kelas Laten (Pengelompokan Prestasi Matematika Siswa Indonesia Berdasarkan Hasil Survey TIMSS)
Abstrak: Conventional methods of clustering become weak when meet measured objects with qualitative or categorical data. Latent class logistic analysis can be an alternative method of clustering to overcome this problem. This research is aim to see the application of latent class logistic analysis to cluster the measured objects with qualitative and quantitative variable and at once to find out backgrounds of the clusters. The objects in this research are 2171 eight grade students from 133 schools in Indonesia. There are two results in this research; first in clustering and second in logistic analysis. In clustering, the students have been clustered into four ideal clusters, e.g. 39.16 percent students were in cluster1, 32.42 percent in cluster2, 21.46 percent in cluster3, and 6.97 percent in cluster4. Each cluster represents the students with very low, low, medium, and high ability in mathematics. In logistic analysis, overall, each cluster has been explained well by covariates e.g. student’s interest, attitude, aptitude and motivation on mathematics, parent’s social-economic condition, parent’s highest education level, teacher’s highest education level, teacher’s major study of mathematics and educations, teacher’s perceptions on schools, school’s facilities, etc.
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Judul: Analisis Diskriminan Logistik untuk Klasifikasi Sekolah Standar Internasional Berdasarkan Status Afiliasi
Abstrak: Affiliate program is one of the government's program to improve the quality of education in Indonesia. The main activity in this program is a partnership with schools in developed countries so that interactions can occur between the components of the school. Implementation of this program need support of the government and society. In order that all support can be utilized maximally, required methods to classify and predict an affiliation status of school. Logistic discriminant analysis is one of the alternatif method to classify which the variables is a combination of numerical and categorical. Logistic discriminant function that used to classify of schools into the particular affiliate status is obtained by logit model predicted as a result of final reduction models.. Through the partial parameter testing, variables that affect the status of affiliation is school type, education of headmaster, and amount of the monthly tuition of international class. The classification accuracy of the discriminant function that is equal to 66.46%.
Keyword: affiliate, logistic discriminant analysis

Judul: Infeksi Virus Parainfluenza Pada Anjing
Abstrak: Virus parainfluenza anjing termasuk famili Paramyxoviridae, berbentuk pleomorf dengan ukuran bervariasi (bergaris tengah antara 100-500 nm), berpembungkus peka ether, berisi genom RNA dan secara serologis mempunyai kesamaan dengan virus SV-5 kera; dikenak sebagai salah satu kausa penting dari sindrom "kennel cough". Infeksinya dapat mengenai anjing semua umur yang belum pernah terinfeksi atau mendapatkan vaksinasi mengakibatkan gejala klinis ringan yang terbatas pada traktus respirasi atu infeksi yang secara klinis tidak memperlihatkan gejala nyata. Gejala klinis yang nampak setelah masa inkubasi (1-5 hari) terlewati berupa batuk yang tidak berat selama beberapa hari, berbagai tingkat tonsilitis dan pharyngitis dan kadang-kadang ditemukan kenaikan temperatur rektal antara 1-2 derajat C dari temperatur normal rat-rata. Anjing terinfeksi mengandung virus pada traktus respirasi bagian atas dan bawah serta limfonoduli sampai hari ke 9 setelah infeksi. Penyebaran virus antar anjing terjadi secara aerogen.
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