Judul: Studi Kasus Ikterus pada Anjing Berdasarkan Hasil Pemeriksaan Darah di Dokter Hewan Praktik “Drh Setyo Widodo dkk”.
Abstrak: Ikterus adalah perubahan warna kekuningan pada sklera mata, membran mukosa, dan kulit. Ikterus dibagi menjadi tiga berdasarkan patofisiologi bilirubin, yaitu ikterus prehepatik, ikterus hepatik, dan ikterus posthepatik. Tujuan dari studi ini untuk mengidentifikasi jenis ikterus berdasarkan hasil pemeriksaan hematologi dan biokimia darah. Pengamatan dilakukan menggunakan data sekunder lima ekor anjing dari salah satu klinik hewan di Bogor. Data yang digunakan berupa temuan klinis dan pemeriksaan darah. Identifikasi jenis ikterus melalui gambaran hematologi dan biokimiawi darah diharapkan dapat mengetahui gambaran variasi kejadian ikterus dan terdapat kemungkinan adanya kombinasi jenis ikterus. Anjing P1 dan P2 mengalam peningkatan kadar bilirubin unconjugated dan peningkatan aktivitas enzim ALT, AST, ALP, dan GGT. Anjing P3 mengalami peningkatan kadar bilirubin unconjugated dan aktivitas enzim hati berupa ALT dan AST. Anjing P4 mengalam peningkatan kedua jenis bilirubin dan aktivitas enzim hati ALT dan AST dan anjing P5 mengalami peningkatan kadar bilirubin conjugated dan penigkatan enzim hati ALP dan GGT. Kesimpulan dari studi kasus ini, anjing P1 dan P2 mengalami ikterus kombinasi berupa ikterus prehepatik, hepatik, dan posthepatik. Anjing P3 memiliki ikterus kombinasi berupa ikterus prehepatik dan hepatik. Anjing P4 mengalami ikterus kombinasi berupa ikterus prehepatik dan posthepatik dan anjing P5 mengalami ikterus posthepatik.
Keyword: biokimiawi darah, enzim hati, hematologi, ikterus, jenis ikterus

Judul: Patogenesis Ikterus pada Kucing: Studi Retrospeksi Berbasis Kasus Klinis.
Abstrak: Ikterus merupakan perubahan warna menjadi kuning pada membran mukosa dan integumen. Ikterus merupakan gejala klinis penting untuk mendeteksi penyakit yang serius pada kucing. Studi ini bertujuan untuk mengidentifikasi jenis ikterus berdasarkan temuan klinis pasien dan menerangkan adanya keterlibatan organ lain melalui penelusuran patogenesis kasus. Ikterus dapat dibagi tiga mekanisme patofisiologis utama yaitu ikterus prehepatik, ikterus hepatik dan ikterus posthepatik. Pengamatan dilakukan dengan menggunakan data sekunder dari 5 ekor kucing di sebuah klinik hewan di Bogor. Temuan klinis yang diperlihatkan pasien dapat menjadi bahan penelusuran patogenesis ikterus. Identifikasi jenis ikterus melalui pendekatan patogenesis pada kasus klinis memberikan gambaran bervariasinya kejadian ikterus dan terdapat kemungkinan adanya kombinasi yang terjadi. Kasus P1,P3 dan P5 kemungkinan mengalami kombinasi antara ikterus hepatik dan posthepatik sedangkan P2 kemungkinan mengalami ikterus hepatik saja. Fungsi pankreas juga terlibat dalam pemeriksaan ikterus, dengan alasan adanya hubungan langsung antara duktus koledukus dan duktus pankreatikus.
Keyword: ikterus, jenis ikterus, kasus klinis, pankreas

Judul: The Construction of Greedy SVP LLL Algorithm
Abstrak: A lattice is a set of all integer linear combination of a set of linearly independent vectors in ℝ𝑛���. The independent vectors are called bases of lattice. Any lattice can be generated from many bases, and these bases have the same cardinality. In the lattice, the most fundamental and renowned problem is the Shortest Vector Problem (SVP). SVP is a tracking problem of the shortest nonzero vector in a lattice with equivalent bases. In two dimensions, SVP problem has resolved exactly by Gauss’ algorithm. When the lattice dimension is higher than two, A.K. Lenstra, H.W. Lenstra and L. Lovasz gave a LLL algorithm to compute approximation of nonzero shortest vector in the lattice. Reduced bases solution obtained from LLL algorithm still be an approximation and has polynomial running time of arbitrary dimension which large enough. In 1994, Schnoor and Euchner modified this LLL algorithm as a new variant which later was named deep insertion LLL algorithm. This algorithm is a modified version of the LLL algorithm to the terms of the exchange step to improve the accuracy of output of LLL reduced bases and applying it to the subset sum problem. The purpose of this research are: (1) Reconstruct the LLL algorithm and deep insertion LLL algorithm using a geometric approach. (2) Construct a greedy SVP LLL algorithm. (3) Implement the three algorithms in a symbolic programming language, and evaluate them experimentally. A bases ℬ=[𝐛���1,𝐛���2,…,𝐛���𝑛���] in ℝ𝑚��� is called reduced LLL with parameter 𝛿��� if satisfies: (a) |𝜇���𝑗���𝑖���|≤12, for every integer 𝑖���,𝑗��� with 1≤𝑖���<𝑗���<𝑛���. (b)𝛿���‖𝜋���𝑗���(𝐛���𝑗���)‖2≤‖𝜋���𝑗���(𝐛���𝑗���+1)‖2, for 𝑗���=1,2,…,𝑛���−1,where 𝛿��� is a reduced parameter of real numbers with 14<𝛿���<1. The first requirement is the reduced basis 𝛿��� must “nearly orthogonal” and in its computation case, this requirement can be reached out by using the Gram-Schmidt’s orthogonalization. While the second requirement is called exchange step, or used to called as Lovasz condition. By using both of these requirements, then they establish the LLL algorithm. Then, Schnoor and Euchner modify the LLL algorithm based on the requirements of the exchange step called the deep insertion LLL algorithm, where the exchange step is based on the comparison of the projected vector in orthogonal complement [𝐛���1,𝐛���2,…,𝐛���𝑘���−1]⊥ after j-th reduction. To construct greedy SVP LLL algorithm, the requirements of the exchange step is based on purely by comparing norm of lattice 𝐛���𝑗��� with norm lattice 𝐛���𝑖��� for 𝑖���=1,2,3…,𝑗���−1. The process of insertion reduced vector after the exchange step also has done greedily. Then, we calculate the number of arithmetic operation in greedy SVP LLL algorithm for further analysis. The result of our exprimentation for three algorithms on the certain matrix size shows that the running time of the three algorithms increases propotional to the size of the matrix. The result also shows that by using 𝛿���=34 for the LLL algorithm and the deep insertion LLL algorithm, and the greedy SVP LLL algorithm which is a new variant made by using no parameter of 𝛿���, outperform of the other of two previous algorithm in terms of speed with the same output.
Keyword: LLL algorithm, LLL deep insertion algorithm, greedy SVP LLL algorithm