Judul: Kajian Keamanan Produk Berbasis Tepung pada Industri Rumah Tangga Pangan (IRTP) di Jawa Barat
Abstrak: Agricultural products as source of food must be safe to protect people from poisoning. According to the data, processed food become the source of food poisoning in 2001-2011. In Indonesia, processed food mostly produced by home industry. Therefore, it was necessary to study the safety assessment of food products produced by home industry. The method applied in this study was problem statement, collecting data and data analysis (determination of area of study, food product and issues on food production in home industry). The data showed that most home industry located in West Java. The products covered all types of NADFC food category and mostly flour-based products. Potential hazard found in flour-based products in West Java were the use of improper flour; use of hazardous materials, food additives excess, and microbial contamination; incorrect processing; packaging and labeling; and storage of food products. It found two types of product that should not categorized as products of home industry and did not comply with national standard.
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Judul: Pengkajian aspek pelabelan dan sanitasi pada industri rumah tangga pangan (IRTP) di Propinsi Daerah Istimewa Yogyakarta:
Abstrak: Setiap orang berhak mendapatkan pangan yang aman dan layak untuk dikonsumsi. Pemerintah Indonesia wajib memenuhi pangan yang aman bagi rakyatnya. Industri Rumah Tangga Pangan (IRTP) sebagai salah satu penghasil pangan dengan jumlah 780.631 industri (BPS 2005) dan tersebar di pelosok nusantara, harus mendapatkan pembinaan dan pengawasan oleh pemerintah agar produk pangan IRTP aman dikonsumsi. Salah satu kendala yang dihadapi IRTP adalah masalah pelabelan pangan dan masalah sanitasi. Laporan audit sarana IRTP terhadap 4194 sarana IRTP (oleh BPOM RI) tahun 2003-2006 menunjukkan bahwa aspek pelabelan masih dalam kondisi yang tidak sesuai dengan PP Pelabelan Pangan. Sedangkan kondisi praktek sanitasi dilaporkan rata-rata dalam kondisi cukup (selang penilaian terdiri atas Baik, Cukup, dan Kurang) . Informasi tentang kondisi praktek sanitasi ini berbeda dengan informasi dalam Kebijakan dan Program Nasional Keamanan Pangan Industri Rumah Tangga, 2003 yang menyatakan bahwa kondisi praktek sanitasi IRTP masih rendah. Penelitian ini bertujuan untuk mengetahui penyebab rendahnya praktek pelabelan IRTP dan mengetahui kondisi sebenarnya praktek sanitasi di IRTP. Tahapan dalam penelitian ini adalah mengkaji peraturan pelabelan, mengakaji materi penyuluhan IRTP, pengumpulan data primer (meliputi data pengetahuan responden tentang pelabelan pangan, data pengetahuan responden tentang sanitasi, data praktek pelabelan pangan IRTP, data praktek sanitasi di IRTP), pengolahan data, pembahasan dan penyusunan rekomendasi.
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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