Judul: Analisis Pemborosan Pangan pada Pasien Rawat Inap di Rumah Sakit PMI Bogor dan Pengaruhnya terhadap Tingkat Kecukupan Gizi
Abstrak: This study was aimed to analize food waste on patients at pmi bogor hospital and it relation with their nutrition and adequency level. A cross sectional study was used in this study. The amount of sample was 38 patients. Data were collected through food recall and interview using a questions. The use 20 patients receiving gastric diet and 18 patients receiving normal diet. Energy and fat adequency level of all respond was above 100%, while for protein and carbohydrate level was abive 50%, while meant that for food provided by the nutrition unit has met for requirement. There was no many food wasted by the patients in PMI hospital. The percentage of left for stapple food 12.4%, animal food 4.8%, vegetable side dish 6.1% and vegetable 7.9%. The food waste in patients of PMI hospital and it relation with their nutrition and adequency level was low.
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Judul: Analysis the Cost and Nutrients of Food Waste Inpatients at UPTD RSUD Bangka Tengah
Abstrak: Salah satu indikator pelayanan makanan rumah sakit adalah persentase sisa makanan pasien ≤20%. Dampak sisa makanan mengakibatkan biaya yang terbuang dan asupan gizi pasien menjadi tidak adekuat. Penelitian dilakukan pada pasien rawat inap UPTD RSUD Bangka Tengah menggunakan metode penelitian cross sectional dengan subjek 48 orang. Hasil penelitian menunjukkan bahwa sisa makanan memenuhi indikator pelayanan gizi (<20%). Rata-rata biaya yang terbuang sebagai sisa makanan per pasien adalah Rp 790,79 per hari atau Rp 284.684,4 per tahun. Zat gizi dalam sisa makanan sebesar 68,73 kalori; protein 2,57 gr; lemak 2,47 gr dan karbohidrat 9,39 gr. Hasil penelitian menunjukkan bahwa terdapat hubungan yang signifikan antara sisa makanan dengan jenis kelamin (p=0,001) dan sisa makanan dengan kelas perawatan (p=0,002). Tidak terdapat hubungan yang signifikan antara sisa makanan dengan usia (p=0,605); sisa makanan dengan jenis perawatan (p=0,388) dan sisa makanan dengan jenis diet (p=0,975)., One of hospital food service indicators is the patient's food waste percentage ≤20%. The impact of food waste results in wasted costs and inadequate nutritional intake of patients. The research was inpatients at UPTD RSUD Bangka Tengah used a cross sectional research method with 48 subjects. The results showed that food waste according to indicator (<20%). The cost average of food waste per patient was Rp 790,79 per day or Rp 284.684,4 per year. Nutrients of food waste were 68,73 calories; protein 2,57 gr; fat 2,47 gr and carbohydrates 9,39 gr. The result showed that there was a significant correlation between food waste with gender (p=0,001) and food waste with inpatient class (p=0,002). There was not significant correlation between food waste with age (p=0,605; food waste with type of hospital care (p=0,388) and food waste with type of diet (p=0,975).
Keyword: cost of food waste, food waste, nutrients of food waste

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