Judul: Audit energi pada pengolahan susu cair menjadi susu bubuk di PT. Ultrindo Intijaya Jakarta
Abstrak: lndustri pengolahan susu merupakan industri pengolahan bahan pangan yang sangat penting bagi peningkatan kualitas sumber daya manusia. Hal ini disebabkan produk olahan susu merupakan bahan pangan bergizi tinggi dengan nutrisi lengkap kebutuhan tuhuh manusia. Diharapkan dengan adanya industri pengolahan susu akan meningkatkan nilai gizi dan ketahanan umur susu sehingga akan mudah dijumpai dipasaran baik bagi konsumen masyarakat perkotaan maupun masyaiakat pedesaan.
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Judul: Audit energi dan penetuan efisisensi energi dalam proses produksi susu evaporasi di PT Ultrindo Intijaya, Jakarta
Abstrak: Sektor industri di Indonesia menempati urutan pertama dalam mengkonsumsi energi nasional, yaitu sebesar 45-48% dari total pemakaian energi nasional dengan peningkatan rata-rata 13.5% setiap tahun. Industri pengolahan susu adalah merupa- kan industri makanan yang padat energi, sehingga untuk mengantisipasi adanya pemborosan dalam sektor ini, tingkat efisiensi dan langkah-langkah penghematan energi sangat diperlukan. Tujuan dari penelitian ini adalah mengetahui kebutuhan energi komersial per- satuan produk dan tingkat efisiensi penggunaan energi pada proses produksi susu bubuk dan susu evaporasi. Dari hasil yang diperoleh ditentukan penghematan energi pada tahapan proses yang terjadi pemborosan dan pemanfaatan energi yang terbuang. Analisis pengolahan data didasarkan pada metode analisis energi Proses dan dibatasi hanya pada energi komersial. Perolehan data meliputi data primer dan data sekunder yang banyak melibatkan proses pindah panas. Perolehan data primer meliputi pengukuran sifat fisik produk, pengamatan spesifikasi peralatan, penguku- ran suhu masuk, suhu keluar dan suhu medium pada tiap tahapan proses untuk perhi- tungan pindah panas yang terjadi, pengukuran lama proses untuk tiap unit produksi dan untuk tiap peralatan yang digunakan, pengukuran pada proses pengeringan, dan pengukuran luasan instalasi pipa. Sedang perolehan data sekunder didapatkan dari pustaka dengan berdasar pada perolehan data primer. ...
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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