Judul: Peranan Kopi Dekafeinasi dalam Menurunkan Risiko Hipertensi : Sebuah Tinjauan Sistematis
Abstrak: Hypertension or increased blood pressure is a degenerative disease with a high prevalence, as well as the biggest cause of premature death in the world. Meanwhile, coffee is a popular and most consumed beverage around the world. Coffee can harm some people with certain health problems including hypertension due to its caffeine content. Decaffeinated coffee is known to be an alternative for people with hypertension with reduced caffeine content up to 97%. However, studies on the role of decaffeinated coffee in decreasing the risk of hypertension are still varied, indicated a systematic review is needed. This study uses a systematic review method to summarize the evidence related to the effect of decaffeinated and regular coffee on the risk of hypertension using Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). The inclusion criteria for scientific journals were determined based on Participants, Intervention, Control, Outcome (PICO). The search using boolean operation resulted in 13 research articles for data extraction. The result revealed that decaffeinated coffee varied between it could decrease or did not give any effect on blood pressure or another biological hypertension marker compared to regular coffee., Hipertensi atau peningkatan tekanan darah merupakan penyakit degeneratif dengan prevalensi tinggi, sekaligus penyebab kematian dini terbesar di dunia. Sedangkan kopi merupakan minuman yang populer dan paling banyak dikonsumsi di seluruh dunia. Kopi dapat membahayakan sebagian orang dengan masalah kesehatan tertentu termasuk hipertensi karena kandungan kafeinnya. Kopi tanpa kafein diketahui bisa menjadi alternatif bagi penderita hipertensi dengan kandungan kafein yang berkurang hingga 97%. Namun, penelitian tentang pengaruh kopi dekafeinasi dalam menurunkan risiko hipertensi masih bervariasi, mengindikasikan perlu dilakukan tinjauan sistematis. Penelitian ini menggunakan metode tinjauan sistematis untuk meringkas hasil penelitian terkait efek kopi tanpa kafein dan kopi biasa terhadap risiko hipertensi menggunakan Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Kriteria inklusi untuk jurnal ilmiah ditentukan berdasarkan Peserta, Intervensi, Pengendalian, Hasil (PICO). Pencarian menggunakan operasi boolean menghasilkan 13 artikel penelitian untuk ekstraksi data. Hasil penelitian menunjukkan bahwa kopi tanpa kafein memberikan efek yang bervariasi antara dapat menurunkan atau tidak berpengaruh pada tekanan darah atau penanda hipertensi biologis lainnya dibandingkan kopi biasa.
Keyword: Coffee, Decaffeinated coffee, Hypertension, Systematic review, Regular coffee

Judul: The relationship between coffee consumption and blood  pressure in the outpatient at Bogor Tengah community health center
Abstrak: The objective of this research was to study the relationship pattern of coffee consumption with the incidence of hypertension in outpatient Bogor Tengah Community Health Center. The design of this study was Case Control in the ratio of cases and controls were 1:1 with a total of 160 subjects. The control subjects were defined who had blood pressure ≤120/≤80 mmHg, while the cases subjects had blood pressure ≥140/≥90 mmHg based on the doctor's diagnosis at least 1 month previously. Pattern coffee consumption data was collected through interviews using a questionnaire containing 15 questions. The habit of drinking coffee in the case group decreased after being diagnosed hypertension and showed a statistically significant difference (p<0,05). Coffee consumption more than 7 cups per week there is not statistically significant with the hypertension (OR=0,677; 95% CI: 0,333–1,378) (p>0,05).
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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