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"Tugas akhir ini secara umum bertujuan untuk membahas latent class model yaitu suatu model yang menghubungkan probabilitas respon suatu individu untuk variabel-variabel indikator dengan suatu variabel laten yang bersifat kategorik. Penaksiran parameter dalam latent class model menggunakan taksiran Maximum Likelihood, yang dicari melalui algoritma EM (Expectation-Maximization). Kecocokan model diuji dengan uji rasio likelihood. Model terbaik dengan banyak kelas optimal dipilih berdasarkan reduksi 2 L , dimana 2 L adalah nilai statistik uji untuk banyak kelas terkait. Berdasarkan banyak kelas yang terbentuk pada model terbaik ini, individu-individu akan dikelompokkan ke dalam kelas-kelas tersebut. Metode tersebut akan diterapkan untuk mencari latent class model dengan tingkatan gejala pasien demam berdarah sebagai variabel laten kategorik yang dibentuk dari 5 variabel indikator kategorik, yaitu transfusi, nadi, tekanan darah, hb darah, dan trombosit. Hasil analisis data menunjukkan bahwa tingkatan gejala demam berdarah dapat dikategorikan menjadi 3 kelas."

"ABSTRAKRanked Set Sampling merupakan salah satu metode pengambilan sampel yang dapat digunakan dalam analisis vegetasi semak. Hal ini dikarenakan metode ini cocok diterapkan pada populasi yang homogen, populasi yang tidak sengaja dibentuk, memiliki mobilitas yang rendah/menetap, serta batas wilayah dan luas wilayahnya dapat ditentukan. Melalui Ranked Set Sampling, dapat diperoleh taksiran rata-rata populasi yang tak bias. Taksiran ini menggunakan informasi awal berupa taksiran rata-rata populasi berdasarkan 1 cycle. Dalam tugas akhir ini, taksiran rata-rata populasi yang diperoleh digunakan untuk menghitung nilai parameter vegetasi. Selanjutnya, nilai parameter vegetasi digunakan untuk memperoleh suatu nilai yang dapat merepresentasikan dominansi suatu spesies tumbuhan terhadap spesies lainnya. Nilai yang diperoleh tersebut disebut dengan Indeks Nilai Penting. Penerapan metode ini dilakukan sebagai ilustrasi dalam menentukan dominansi spesies semak pada Hutan Kota Wales Barat Universitas Indonesia.

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ABSTRAKRanked Set Sampling is one of the sampling methods which can be applied in analysis of shrubs vegetation. This is because the method suits the homogeneous, population unintentionally formed, has low mobility kind of population; in which the borders and area can be determined. By using Ranked Set Sampling, unbiased estimator of mean population can be obtained. These estimations use the initial information of mean population estimator based on 1 cycle. In this paper, the estimated mean population that is obtained is used to calculate vegetation parameter value. Furthermore, the vegetation parameter value is used to obtain a value that can represent the domination of one species of plant over others. The obtained value is called Importance Value Index. The application of this method is performed as an illustration of determining the domination of shrubs species in Hutan Kota Wales Barat, Universitas Indonesia."

"The Third Edition retains the general organization of the prior two editions, but it incorporates new material throughout the text. The book is organized into six parts: Part I covers basic sampling from simple random sampling to unequal probability sampling; Part II treats the use of auxiliary data with ratio and regression estimation and looks at the ideas of sufficient data, model, and design in practical sampling; Part III covers major useful designs such as stratified, cluster and systematic, multistage, and double and network sampling; Part IV examines detectability methods for elusive populations, and basic problems in detectability, visibility, and catchability are discussed; Part V concerns spatial sampling with the prediction methods of geostatistics, considerations of efficient spatial designs, and comparisons of different observational methods including plot shapes and detection aspects; and Part VI introduces adaptive sampling designs in which the sampling procedure depends on what is observed during the survey. For this new edition, the author has focused on thoroughly updating the book with a special emphasis on the first 14 chapters since these topics are invariably covered in basic sampling courses. The author has also implemented new approaches to explain the various techniques in the book, and as a result, new examples and explanations have been added throughout. In an effort to improve the presentation and visualization of the book, new figures as well as replacement figures for previously existing figures have been added. This book has continuously stood out from other sampling texts since the figures evoke the idea of each sampling design. The new figures will help readers to better visualize and understand the underlying concepts such as the different sampling strategies."