Judul: Deteksi Status Mineral Pada Ayam Petelur Melalui Pengamatan Kandungan Mineral Telur Dan Biokimia Pada Darah
Abstrak: Serangkaian penelitian telah dilakukan di Fakultas Peternakan Institut Pertanian Bogor, untuk mempelajari metode pendugaan status mineral pada ayam petelur melalui pengamatan penampilan produksi, kandungan mineral telur dan pengamatan biokimia pada darah. Percobaan dilakukan dengan menggunakan Rancangan Acak Lengkap (RAL) terdiri dari empat perlakuan dan tiga ulangan. Tiga macam ransum defisien mineral masing-masing mengandung 25, 50 dan 75 persen dedak padi dan satu macam kepada tujuan ransum komersial sebagai kontrol telah diberikan 168 ekor ayam petelur selama dua bulan, untuk mempelajari pengaruh defisiensi terhadap penampilan produksi, kandungan mineral dengan mineral (Ca, P, Mg, Fe, Cu, Mn, dan Zn) pada kulit telur, kuning telur, serum dan tulang serta aktivitas enzim alkalin fosfatase Percobaan dilanjutkan dengan suplementasi multi mineral selama empat bulan, dengan tujuan untuk mengetahui kemampuan ayam petelur dalam memperbaiki penampilan prouksinya. Hasil yang diperoleh dalam penelitian ini menunjuk- bahwa defisiensi mineral secara nyata dapat menye- kan babkan terjadinya penurunan rataan konsumsi ransum, pro- duksi telur dan bobot telur pada bulan pertama terjadinya defisiensi. Suplementasi mineral dapat meningkatkan kembali rataan konsumsi ransum, produksi telur dan bobot telur, namun proses pemulihan ini memerlukan waktu yang cukup lama,….dst
Keyword: Mineral Status, Laying hens, Egg Mineral Content, Blood Biochemistry

Judul: Organic Mineral Mixed Suplementation in Feed on Isa Brown Laying Hens Performance and Quality 90-97 Weeks
Abstrak: Penelitian ini bertujuan mengevaluasi suplementasi campuran mineral organik dalam pakan pada ayam petelur . Penelitian menggunakan 1444 ekor ayam. Penelitian ini menggunakan rancangan acak lengkap (RAL) dengan 2 perlakuan dan 11 ulangan. Perlakuan yang digunakan adalah T0 = pakan komersial, dan T1 = pakan komersil + campuran mineral organik. Parameter yang diamati terdiri dari warna kerabang, kekuatan kerabang, ketebalan kerabang, haugh unit, hen day production, konsumsi pakan, bobot telur, dan konversi pakan. Data dianalisis menggunakan uji T. Hasil penelitian berpengaruh nyata meningkatkan hen day production, konversi pakan, konsumsi pakan, warna kerabang, ketebalan kerabang, dan kekuatan kerabang (P <0,05), namun tidak berpengaruh pada bobot telur dan haugh unit (P >0,05). Penerapan suplementasi campuran mineral organik dapat meningkatkan hen day production, konsumsi pakan, konversi pakan, kekuatan kerabang, warna, ketebalan kerabang telur ayam petelur strain Isa Brown, namun belum mampu meningkatkan haugh unit dan bobot telur., This study was aimed to evaluate supplementation of organic mineral mix in feed for Isa Brown hens. The study used 1444 chickens. This study used a completely randomized design (RAL) with 2 treatments and 11 replications. The treatments used were T0 = commercial feed and T1 = commercial feed + organic mineral mixture. Parameters observed consisted of shell color, shell strength, shell thickness, haugh unit, hen day production, feed consumption, egg weight, and feed conversion. Data were analyzed using T test. The results showed that significantly improved hen day production, feed conversion, feed consumption, shell color, shell thickness, and shell strength (P <0,05), but had no effect on egg weight and haugh unit (P >0,05). The application of organic mineral mixture supplementation can increase hen day production, feed consumption, feed conversion, shell strength, color, egg shell thickness of laying hens strain Isa Brown, but has not been able to increase the haugh unit and egg weight.
Keyword: Laying hens final phase of production, Performance

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