Judul: Kajian Metode Penggerombolan Dua Tahap untuk Data yang Mengandung Pencilan
Abstrak: Cluster analysis is often encountered in various studies. Analysis of classical clusters, such as hierarchical clustering method and k-means clustering cannot handle categorical variables or a mixture of numerical and categorical. In addition, the determination of the optimal number of clusters are still dependent on the subjectivity of the researcher and cannot handle very large datasets, which is larger than 500. One approach to addressing this problem is to use a two-step clustering method. The accuracy of the two-step clustering method of predicting the number of clusters generated as well as the classification of cluster membership, especially in the data containing outliers is important to be studied. Outliers in the data containing a small (1%), this method provides more accurate compared with the results of data containing a large outliers (5% or 15%). Scale use of outliers handling in the data containing outliers must be greater than the amount of outliers itself. Two-step clustering method is very accurate in producing a number of clusters associated with the actual number of population clusters that do not contain data outliers, especially in the most variable of type numeric and categorical rest. Clustering villages in Indonesia by a factor of progress and backwardness villages using a two-step clustering method generates optimal cluster 7.
Keyword: two-step clustering method, data outliers, cluster analysis

Judul: Penerapan metode penggerombolan berdasarkan gaussian mixture models dengan menggunakan algoritma expectation maximization
Abstrak: Model-based clustering bertujuan untuk mengoptimalkan kemiripan antara individu dengan menggunakan pendekatan model probabilistik. Keseluruhan data diasumsikan berasal dari campuran dua atau lebih sebaran peluang dengan proporsi tertentu. Data dapat digerombolkan dengan menggunakan Gaussian Mixture Models (GMM), yaitu mixture dari G sebaran peluang Gaussian. Masing-masing sebaran mewakili suatu gerombol dengan parameter tertentu. Parameter tersebut diduga menggunakan algoritma Expectation Maximization (EM) dengan nilai awal parameter diperoleh dari agglomerative hierarchical clustering. Metode ini menggunakan Bayes Information Criterion (BIC) untuk menentukan jumlah gerombol terbaik dengan berbagai karakteristik geometrik matriks peragam dari sebaran Gaussian. Dalam penelitian ini, GMM diterapkan pada beberapa pola sebaran data. Data dibangkitkan dari sebaran Gaussian dengan beberapa kondisi parameter, antara lain parameter vektor rataan dan matriks peragam ketiga gerombol identik, vektor rataan ketiga gerombol identik dengan matriks peragam yang berbeda, vektor rataan yang berbeda dengan matriks peragam yang identik, dan terakhir adalah parameter vektor rataan dan matriks peragam yang berbeda. Keefektifan GMM pada data tersebut dapat diketahui dengan menghitung rataan tingkat kesalahan klasifikasi. Kondisi lain yang dipertimbangkan dalam membangkitkan data adalah jarak antar pusat gerombol dan keragaman setiap gerombol untuk melihat keefektifan metode jika ketiga gerombol saling berjauhan, saling berdekatan, maupun saling tumpang tindih.
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Judul: Gambaran darah komodo (Varanus komodoensis) di Taman Margasatwa Ragunan
Abstrak: This study was conducted to get the hematology and blood biochemistry profile of Komodo dragons at Ragunan Zoo. A total of 18 adult dragons were used. Blood was drawn as much as 2 mL whole blood for hematology and 3 mL for blood biochemistry in serum. Hematology examinations were done by automatic hemavet® machine except differential leukocytes were done manually and blood biochemistry examinations were done by biosystem® machine. Examinations results of erythrocyte parameters of total erythrocytes, hematocrit, hemoglobin, MCV, MCH, and MCHC in row are (1,24±0,21) × 106/mm3, (38,0±4,6) %, (13,3±1,6) g/dL, (311,4±49,9) fL, (109,4±18,7) pg, and (35,1±1,2) g/dL. Trombocytes count is (3,1±1.6) × 103/mm3 and erythrocyte sedimentation rate is (3,9 ± 1.7) mm/h. Leukocytes parameters indicate the values of total leukocytes, heterophils, lymphocytes, monocytes, eosinophils, and basophils in row are (6,53±9,47) × 103/mm3, (3,478±4,972) × 103/mm3, (2,959±4,694) × 103/mm3, (0,096±0,187) × 103/mm3, (0,00) /mm3, and (0,00) /mm3. Biochemical parameters indicate the values of total protein, albumin, globulin, AST, ALT, urea, and creatinine in row are (10,19±3,39) g/dL, (2,51±0,39) g/dL, (7,68±3,07) g/dL, (49,39±20,71) IU/L, (45,39±27,88) IU/L, (13,53±5,88) mg/dL, and (0,29±0,11) mg/dL. The result of examinations averagely showed values tend to normal. Some individual results demonstrated abnormalities which are suspected as acute infection in 1 dragon, foliculogenesis in 1 dragon, muscle disease in 2 dragons, and liver disease in 5 dragons.
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