Judul: Analisis Biologi Berbasis Deret Waktu Pada  Sampel Feces Monyet Ekor Panjang
Abstrak: Long-tailed macaques (Macaca fascicularis) are valuable in forensic laboratory tests due to their similarities to humans. This study analyzed biological changes in macaque fecal samples over 24 hours, highlighting the need for fresh samples for accurate diagnostics. Ten healthy macaque fecal samples were examined using macroscopic examination, fluorescence imaging, and protein content assessment via the Bradford method. Results showed no significant changes in color and size, but consistency decreased from 4 to 6-hours, then increased at 8-hours. Odour score decreased initially, then increased at 8-hours. The fluorescent particle number rose up to 4-hours, then gradually decreased from 6 to 24-hours. The highest fluorescent color intensity was at 8-hours, with the lowest at 16-hours. Fluorescent particle size significantly increased at 6-hours and decreased at 16-hours. The protein content significantly rose after 2-hours, remained stable until 20-hours, and then decreased by 24-hours. No correlation was found between protein content and macroscopic examination (color, consistency, odour, size). This study underscores the dynamic biological changes in macaque fecal samples over 24 hours and the importance of using fresh fecal for accurate diagnostics., Monyet ekor panjang (Macaca fascicularis) memiliki nilai penting dalam uji laboratorium forensik karena kesamaannya dengan manusia. Studi ini menganalisis perubahan biologis dalam sampel tinja monyet selama 24 jam, menekankan perlunya sampel segar untuk diagnosis yang akurat. Sepuluh sampel tinja monyet sehat diperiksa menggunakan pemeriksaan makroskopis, pencitraan fluoresensi, dan penilaian kandungan protein dengan metode Bradford. Hasil menunjukkan tidak ada perubahan signifikan dalam warna dan ukuran, tetapi konsistensi berkurang dari 4 hingga 6-jam, kemudian meningkat pada 8-jam. Skor bau berkurang pada awalnya, kemudian meningkat pada 8-jam. Jumlah partikel fluoresen naik hingga 4-jam, kemudian secara bertahap menurun dari 6 hingga 24-jam. Intensitas warna fluoresen tertinggi adalah pada 8-jam, dengan yang terendah pada 16-jam. Ukuran partikel fluoresen meningkat secara signifikan pada 6-jam dan menurun pada 16-jam. Kandungan protein naik secara signifikan setelah 2-jam, tetap stabil hingga 20-jam, dan kemudian menurun pada 24-jam. Tidak ditemukan korelasi antara kandungan protein dan pemeriksaan makroskopis (warna, konsistensi, bau, ukuran). Studi ini menekankan perubahan biologis dinamis dalam sampel tinja monyet selama 24 jam dan pentingnya menggunakan tinja segar untuk diagnosis yang akurat.
Keyword: fecal samples

Judul: Pengaruh pemberian pakan tepung dan minyak Ikan Lele, serta Probiotik E. faecium IS-27526 terhadap profil darah Macaca fascicularis betina usia tua
Abstrak: Penelitian ini bertujuan menganalisis pengaruh pemberian pakan tepung ikan lele, minyak ikan lele, serta probiotik E. faecium IS-27526 terhadap profil darah monyet ekor panjang (MEP) betina usia tua. Desain penelitian yang digunakan adalah experimental study selama 90 hari. Contoh dalam penelitian ini berjumlah 9 ekor MEP yang telah mengalami masa adaptasi selama 45 hari. Peneliti membagi contoh ke dalam tiga perlakuan, yaitu kelompok tepung ikan lele (A1), kelompok tepung ikan lele + probiotik (A2), dan kelompok tepung ikan lele + probiotik + minyak ikan (A3). Hasil uji sidik ragam menunjukkan bahwa terdapat perbedaan yang nyata (p<0.05) antara perlakuan dengan perubahan kadar eritrosit, hemoglobin, dan hematokrit. Namun, tidak terdapat perbedaan yang nyata (p>0.05) antara perlakuan terhadap perubahan nilai MCV, MCH, MCHC, leukosit, dan trombosit. Lama intervensi dan interaksi perlakuan dengan lama intervensi juga tidak berpengaruh nyata terhadap profil darah monyet ekor panjang., The aim of this study was to analyze the effect of catfish flour, catfish oil, and probiotic E. faecium IS-27526 based on blood profile of aged female long-tailed monkeys. Experimental design was applied for this study. Feeding trial was conducted in 90 days. Nine monkeys had been conditined on 45 days before this study begun and they were divided into 3 groups of treatment: catfish flour (A1), catfish flour + probiotic (A2), and catfish flour + probiotic + catfish oil (A3). The statistical analysis using ANOVA test showed that significant difference exist (p<0.05) between treatment to the change level of erythrocytes, hemoglobin, and hematocrit. However, no significant difference (p>0.05) were observed between treatment to the change level of MCV, MCH, MCHC, leukocytes, and thrombocytes. The result also showed that the duration of intervention and intervention treatment vs duration of intervention had no significant difference on blood profile of the samples.
Keyword: profil darah, tepung ikan lele, minyak ikan lele, probiotik, Macaca fascicularis

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