Judul: Pengklasifikasian Propolis Lebah Madu Trigona spp. dari Empat Wilayah di Indonesia dengan Menggunakan Pendekatan Metabolomik Berbasis FTIR
Abstrak: Propolis is a resinous substance collected by honeybees from various plant sources. Propolis obviously possesses antioxidant activity, as reported by many researchers. Although numerous researchers have reported the biological activities of propolis collected worldwide, information about Indonesian propolis, particularly from Trigona spp., is only a few. Some studies reported that propolis has various bioactivities including antimicrobial, anticancer and antioxidant. These properties are influenced by phenols and flavonoids compounds.. The complex constituents and properties of propolis is different from each other depends on location and plant of origin. This variation will have an effect on its bioactivity. Indonesia has many local honey bees; one of them that produce propolis is Trigona spp. The location of propolis source used in this research may relate to its physical and chemical characteristics. Some researches have examined the correlation between phenol and flavonoid content with antioxidant activity of propolis. It was found that for some cases there is no correlation which implies that other compounds may have influence to the antioxidant activity. Therefore metabolomic is further used to observe this possibility. Metabolomic approach is capable of determination which regions have a potential propolis as a source of antioxidant. Metabolomic is defined as metabolite process analysis of the organism comprehensively quantitatively or qualitatively. Metabolomic approach in this study is focussed on classification of propolis as a result the difference of regions and its correlation to antioxidant activity. The objective of this research is to apply metabolomic in classification of propolis from four regions based on its FTIR metabolite profile and its antioxidant activity. Those four regions are West Nusa Tenggara, West Java, West Kalimantan and South Sulawesi. Since the composition of propolis varies with its origin, the intensity of antioxidant activity should be different as well. Metabolomic approach was used to identify which region has propolis with better antioxidant activity. FTIR based metabolomic was applied to measure the spectra of propolis in order to examine the differences among propolis samples then to classify them. For this purpose, the FTIR spectra were analyzed by PCA and PLS. In addition, the correlation between propolis phenol and flavonoid content to its antioxidant capacity was also determined. Interpretation of FTIR spectra showed the presence of O-H, C-O and C-H aromatic bond for phenol and its ester. Meanwhile, the presence of flavonoid compound is designated to C=O, C-H, C-H aromatic and supported by O-H bond. In addition, C=C, C-O bonds were also found which may relate to the presence of terpenes. The samples also confirm the presence of N-O symmetric, C-N and N-H which point to amino acid and aromatic amine. There were also C-O and O-H bonds which may relate to fatty acid. Nevertheless the existence of these compounds according to the functional groups is not confirmed yet. Then further confirmation by targeted analysis of propolis total phenol and flavonoid content and its correlation to propolis antioxidant activity are required. Antioxidant potential of propolis from four regions in Indonesia was accessed by analyze propolis scavenging effect on DPPH radicals which IC50 were in the range 0,54-2,90 μg/mL. Low values of IC50 on
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Judul: Kandungan Fitokimia dan Toksisitas Propolis Lebah Trigona spp. Asal Propinsi Banten, Jawa Barat, Jawa Tengah, NTB dan Maluku
Abstrak: Kekayaan sumber daya hayati Indonesia berpotensi menghasilkan bahan yang dapat dimanfaatkan sebagai nutraceutical dan pangan fungsional, salah satunya adalah propolis yang berasal dari lebah lokal yang tidak menyengat Trigona spp. Penelitian ini bertujuan untuk mengidentifikasi senyawa fitokimia secara kualitatif dan menilai tingkat toksisitas ekstrak propolis sebagai pangan fungsional atau nutraceutical. Propolis diekstrak dari propolis mentah yang berasal dari propinsi Banten, Jawa Barat, Jawa Tengah, Nusa Tenggara Barat (NTB), dan Maluku. Analisis fitokimia secara kualitatif dilakukan untuk mengidentifikasi keberadaan kelompok senyawa alkaloid, flavonoid, tanin, dan saponin. Metode Brine Shrimp Lethality Test (BSLT) digunakan untuk menilai tingkat toksisitas ekstrak propolis. Kelima sampel positif mengandung senyawa flavonoid, tanin, dan saponin namun tidak terdeteksi adanya kelompok senyawa alkaloid. Hasil perhitungan uji keamanan pangan dengan nilai LC501, sampel ekstrak propolis dari propinsi Banten memberikan sifat toksik tertinggi dibanding dengan ekstrak propolis dari propinsi lainnya. Berdasarkan perhitungan estimasi nilai LD502 untuk berat badan contoh 60 kg, semua sampel uji propolis aman dikonsumsi sebanyak 18-60 ml/hari, kecuali ekstrak propolis dari propinsi Banten sebanyak 3.6 ml/hari
Keyword: BSLT, fitokimia, keamanan pangan, propolis

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