Judul: Identifikasi Enteropatogen sebagai Dasar Manajemen Diare Monyet Ekor Panjang di Fasilitas Penangkaran IPB Dramaga
Abstrak: Macaca fascicularis atau monyet ekor panjang (MEP) merupakan salah satu satwa primata yang digunakan sebagai hewan laboratorium dan/atau hewan model dalam penelitian biomedis. Diare merupakan salah satu masalah karena menyebabkan angka morbiditas dan mortalitas yang cukup tinggi, serta perlu diatasi dengan baik dalam manajemen kesehatan satwa primata di penangkaran. Ketuntasan pengendalian diare membutuhkan intervensi klinis untuk menghasilkan konsep manajemen diare, sehingga penelitian ini dilakukan untuk 1) mengidentifikasi enteropatogen dari sampel feses, pakan, dan sumber air minum, 2) menyusun langkah intervensi klinis, dan 3) merumuskan konsep manajemen diare MEP. Sampel penelitian dikoleksi dari fasilitas penangkaran monyet ekor panjang IPB Dramaga yang terdiri dari: 1) feses (n=30) untuk identifikasi enterobakteria, rotavirus dan endoparasit, 2) air (n=6) dan pakan (n=2) diuji untuk mengetahui jumlah Escherichia coli dan coliform. Isolat enterobakteria yang didapat dilakukan pengujian resistensi antibiotik untuk menentukan sensitivitasnya terhadap berbagai antibiotika. Pengambilan sampel feses diawali dengan pengamatan kejadian diare selama seminggu pada setiap kandang (total 18 kandang dengan 310 ekor MEP) dan kembali diamati selama seminggu setelah pemberian pengayaan lingkungan (penambahan rantai untuk brachiasi dan drum plastik). Total kejadian diare pada MEP di fasilitas penangkaran IPB Dramaga adalah 9.67%. Bakteri dari sampel feses teridentifikasi E. coli 100% (30/30), Salmonella enteritidis 97% (29/30), dan Shigella sp. 60% (18/30), serta rotavirus tidak teridentifikasi. Endoparasit yang teridentifikasi antara lain Strongyloides sp., Trichuris sp., dan Entamoeba sp. masing-masing dari satu sampel (3.33%), serta Balantidium coli 23.33% (7/30). Kontaminasi E. coli dan coliform pada sampel air dan pakan (pisang dan monkey chow) berada di atas batas minimum. Bakteri enteropatogen yang teridentifikasi memiliki sensitivitas yang baik terhadap siprofloksasin dan gentamisin, serta resistensi tertinggi terhadap eritromisin. Pengayaan lingkungan pada koloni MEP dengan jumlah hewan kurang dari 10 ekor mengalami penurunan kejadian diare sebesar 1%, sedangkan koloni dengan jumlah 10-20 ekor mengalami penurunan kejadian diare sebesar 10%. Oleh karena itu, manajemen diare perlu secara konsisten dilakukan antara lain 1) intervensi air dengan klorinasi untuk mengurangi jumlah bakteri, 2) penanganan pakan yang baik pada gudang penyimpanan, 3) melakukan sanitasi dengan desinfektan sesuai dengan standar baku di penangkaran, 4) pengobatan diare secara intensif pada individu MEP berupa terapi cairan dan antibiotik, dan 5) pencegahan endoparasit dengan memberikan ivermectin dan metranidazol setiap tiga bulan sekali.
Keyword: antibiotik, diare, enteropatogen, monyet ekor panjang, manajemen

Judul: Identifications of Gastrointestinal Parasites in Long-Tailed Monkey (Macaca fascicularis) at The Primate Research Center of IPB  University
Abstrak: Infeksi parasit merupakan salah satu masalah yang sering ditemukan pada satwa primata, termasuk monyet ekor panjang (Macaca fascicularis). Infeksi parasit pada saluran pencernaan perlu diwaspadai karena dapat mengganggu kesehatan monyet ekor panjang di penangkaran dan berpotensi menjadi sumber penyakit zoonotik yang dapat menyebar kepada manusia. Penelitian ini bertujuan mengidentifikasi parasit gastrointestinal pada feses monyet ekor panjang di Pusat Studi Satwa Primata (PSSP) IPB. Sebanyak 69 sampel feses monyet ekor panjang diperiksa menggunakan metode natif dan pewarnaan trichrome untuk mengidentifikasi parasit. Hasil pemeriksaan menunjukkan bahwa terdapat Entamoeba spp., E. polecki, E. coli, E. histolytica/E. dispar, Endolimax nana, Balantidium coli, Iodamoeba bütschlii, Giardia sp., dan Ancylostomatidae, yang diduga bersumber dari air yang digunakan di PSSP IPB. Perubahan konsistensi feses diduga diakibatkan faktor selain infeksi parasit., Parasitic infection is a problem that is often found in nonhuman primates, including the long-tailed monkey (Macaca fascicularis). Parasitic infections in the digestive tract need to be concerned because they can interfere with the well-being of long-tailed monkeys in captivity and have the potential to become a source of zoonotic diseases that can spread to humans. This study aims to identify gastrointestinal parasites in long-tailed monkey feces at the Primate Research Center of IPB University. A total of 69 samples of long-tailed monkey feces were examined using native method and trichrome staining to identify parasites. The results showed that there were Entamoeba spp., E. polecki, E. coli, E. histolytica/E. dispar, Endolimax nana, Balantidium coli, Iodamoeba bütschlii, Giardia sp., and Ancylostomatidae, allegedly derived from the water in PSSP IPB. Change in stool consistency is assumed to be due to factors other than parasitic infection.
Keyword: long-tailed monkey, gastrointestinal parasites, Macaca fascicularis, zoonoses

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