Judul: Analysis of the Effect of Opening on indoor Thermal Comfort in Residential Houses in Dramaga Cantik Housing
Abstrak: Rumah tinggal berguna sebagai tempat berlindung dan beristirahat bagi manusia, sehingga perlu mempertimbangkan kenyamanan termal. Penelitian ini bertujuan untuk mengevaluasi kondisi termal pada bangunan tempat tinggal dan mengidentifikasi sejauh mana pengaruh bukaan dalam membantu mencapai kenyamanan termal. Penelitian ini dilakukan dengan mengukur temperatur udara secara langsung serta simulasi menggunakan software Ecotect Analysis 2011. Simulasi dilakukan pada dua kondisi yaitu kondisi aktual dan kondisi modifikasi bukaan. Hasil penelitian menunjukkan bahwa rumah tinggal obyek studi tidak memenuhi kenyamanan termal dengan temperatur udara berkisar antara 26,5 oC – 30,6 oC. Perbandingan hasil simulasi Ecotect Analysis dengan pengukuran temperatur udara secara langsung didapatkan nilai R2 sebesar 0,8113 yang berarti tingkat akurasi simulasi sangat kuat. Modifikasi bukaan yang disimulasikan berupa penggantian serta penambahan jendela. Hasil simulasi kondisi modifikasi menunjukkan temperatur udara dalam rumah mengalami penurunan dengan nilai berkisar antara 23,5 oC – 27,1 oC dan telah memenuhi kenyamanan termal.
Keyword: air temperature, aperture, relative humidity, thermal comfort

Judul: Analysis Of Thermal Comfort Using Modern Building Material In Baduy Dalam House With Computational Fluid Dynamic
Abstrak: Eco-house is the applying of an ecological design on building. In Indonesia, Baduy Dalam community are examples of people who still have and perform local knowledge in their lifestyle including implementing ecological design in their homes. In this research, has been performed an analysis of thermal comfort in Baduy Dalam homes. The analysis had been performed by using three combinations of roof, wall and floor materials in Baduy Dalam’s house which are ceramic- brickceramic; concrete-brick- ceramic and asbestos cement-brick-ceramic. The analysis performed by a simulation techniques using a computer program Computational Fluid Dynamic (Solidworks 2011) to get a distribution model of air temperature, air movement, and relative humidity(RH) in the building. The input of environmental data such as temperature, RH, solar radiation, and wind speed used a 13 November 2010’s datas. The simulations carried out at 11:00, 13:00, 15:00, 19:00, 21:00, and 23:00. The simulation results of the most unsatisfied thermal comfort conditions using a combination 1 materials are; temperature 55.52°C, RH 20.71%, air flow 0.064 m/s, combination 2 are temperature 59.58°C, RH 17.10%, air flow 0.085 m/s, and combination 3 are; temperature 50.56°C, RH 24.14%, and air flow 0.065 m/s. The simulation results show that the worst conditions are combination 2 (concrete roof, brick walls and cement floor). The highest temperature is 59.58 ° C at 13:00. Modifications is made to the worst house condition by adding vents on the Baduy Dalam house and the results are temperature was -22.07°C lower at Imah and -22.24°C lower at Tepas.
Keyword: 

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