Judul: Physical and Organoleptic Properties of kefir from cow’s milk Supplemented by Red Fruit Extract (Pandanus conoideus)
Abstrak: Kefir susu sapi merupakan produk susu fermentasi menggunakan starter biji kefir yang terdiri dari bakteri asam laktat, kapang, dan khamir. Kefir memiliki manfaat bagi kesehatan karena termasuk dalam pangan probiotik. Kefir juga mengandung eksopolisakarida dan peptida bioaktif yang dapat meningkatkan sistem imun tubuh. Buah merah adalah buah endemik dari Papua yang memiliki manfaat juga bagi kesehatan karena mengandung zat aktif yang dapat meningkatkan sistem imun tubuh. Zat aktif yang terkandung dalam buah merah adalah karotenoid, alfa tokoferol, beta karoten, asam linoleat, asam oleat, asam linolenat, dan asam dekanoat. Tujuan penelitian ini adalah menganalisis sifat fisik dan organoleptik kefir susu sapi dengan penambahan ekstrak buah merah 0%, 2,5% dan 5%. Analisis sifat fisik yang diuji adalah viskositas, nilai pH, nilai aw, dan total asam tertitrasi. Analisis sensori yang dilakukan adalah uji hedonik dan uji mutu hedonik. Hasil penelitian menunjukan penambahan ekstrak buah merah berpengaruh nyata (P < 0,05) terhadap nilai viskositas, total asam tertitrasi, uji hedonik parameter warna, dan aroma serta uji mutu hedonik parameter warna, aroma, dan kekentalan, namun tidak berpengaruh nyata (p > 0,05) terhadap nilai aw, nilai pH, uji hedonik parameter rasa dan kekentalan serta uji mutu hedonik parameter rasa., Cow's milk-based kefir is a fermented milk product that uses kefir grains utulizing of lactic acid bacteria (LAB) and yeast combination as fermentation starter. Kefir is very beneficial for health because it contains probiotic active exopolysaccharides and bioactive peptides that can stimulate the body's immune system. Red fruit (Pandanus conoideus) is an endemic fruit of Papua which had known to have various health benefit effects. Red fruit contains bioactive compounds which can boost the immune system. The compounds include carotenoids, alpha-tocopherol, beta carotene, linoleic acid, oleic acid, linolenic acid, and decanoic acid. This studsy aims to analyze the physical and organoleptic properties of cow's milk-based kefir with the addition of 0%, 2.5%, and 5% red fruit extract. The tested physical properties were viscosity, pH value, aw value, and total titrated acid, coupled with the sensory analysis through hedonic test and the hedonic quality test. The results showed that the addition of red fruit extract had a significant effect (P < 0,05) on the viscosity value, total titrated acid, the hedonic test for color and aroma parameters, and the hedonic quality test for color, aroma, and viscosity parameters, but had no significant effect (p > 0,05) on aw, pH, taste, and viscosity parameter hedonic test, and taste parameter hedonic quality test.
Keyword: Kefir, organoleptic, physical properties, red fruit extract

Judul: Chemical Properties and Total of Lactic Acid Bacteria of Cow’s Milk Kefir with Addition of Red Fruit Extract  (Pandanus Conoideus Lam).
Abstrak: Kefir merupakan produk susu fermentasi yang menggunakan bakteri asam laktat dan ragi. Susu sapi dipilih karena susu sapi merupakan zat pelengkap yang kaya akan nutrisi seperti protein, lemak, vitamin, mineral dan karbohidrat. Buah merah berfungsi sebagai aditif dalam makanan untuk meningkatkan nilai gizi, dan bekerja sebagai antimikroba. Penelitian ini bertujuan menguji sifat kimiawi dan total bakteri asam laktat pada kefir susu sapi dengan penambahan buah merah. Penambahan buah merah sebesar 0%, 2,5% dan 5% dari total ekstrak buah merah dalam pembuatan kefir. Rancangan analisis statistik yang diujikan adalah rancangan acak lengkap (RAL) dengan perlakuan penambahan ekstrak buah merah pada konsentrasi yang berbeda dengan tiga kali ulangan yaitu pertama tanpa penambahan buah merah atau kefir 100% sebagai kontrol; penambahan kedua ekstrak buah merah 2,5%; penambahan ketiga ekstrak buah merah 5%. Hasil menunjukkan bahwa perbedaan persentase penambahan ekstrak buah merah pada formula kefir susu sapi tidak berpengaruh nyata (P>0.05) terhadap semua analisis kimia dan total bakteri asam laktat kecuali pada total asam tertitrasi berpengaruh nyata (P<0.05)., Kefir is a fermented milk product that uses lactic acid bacteria and yeast. Cow milk is the most prefereable raw material for kefir production due to its high nutrition content including protein, fat, vitamins, minerals and carbohydrates. Red fruit functions as an additive in food to increase nutritional value, and works as an antimicrobial. It leads to an assumption that the use of red fruit might be able to increase the functionality of kefir. The addition of red fruit by 0%, 2.5%, 5% of the total red fruit extract in the manufacture of kefir, the chemical analysis observed was the percentage of total protein, total fat, water content, ash content and total acid titrated. The microbiological analysis observed was the total lactic acid bacteria. The experiment was done under a completely randomized design. The data analysis was done under a one-way ANOVA. The results showed that the difference in the percentage of the addition of red fruit extract to the goat's milk kefir formula had no significant effect (P> 0.05) on all chemical analyzes and the total LAB except for TAT had a significant effect (P <0.05).
Keyword: Buah Merah, Kefir, Susu Sapi

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