Judul: Kajian pengeringan manisan pepaya (Carica papaya) menggunakan hot air rotary oven., Asessments of drying of candied papaya (Carica papaya) by using hot air rotary oven
Abstrak: Papaya is a fruit that is easily damaged and relatively has low shelf life. To increase the added value of papaya, this fruit is dried to become dry candied papaya. The objective of this research is to assess the performance of hot air rotary oven dryer on candied papaya drying process and determine the optimum temperature for drying process of candied papaya. Papaya fruit with varieties of Calina IPB-9 with the maturity level of 80 % is used as a raw material for making candied papaya. The treatments that conducted were blanching temperature and drying temperature. The blanching temperatures are 80 °C and 90 °C while the drying temperatures are 45, 60, and 75 °C. The results showed that blanching temperature have no effect on the candied papaya drying process while drying temperature could accelerate the drying rate. Candied papaya that treated by blanching temperature of 80 °C and drying temperature of 60 °C resulting in the best quality based acceptance of taste’s criteria.
Keyword: optimum temperature., dryer, candied papaya, papaya

Judul: Rekayasa proses pengeringan untuk produksi buah pepaya kering Dried carica papaya
Abstrak: Komoditas hortikultura merupakan salah satu komoditas hasil pertanian yang memiliki nilai ekonomi tinggi. Penanganan pra dan pasca panen merupakan faktor penting untuk meningkatkan pemanfaatan pepaya. Kurang lebih 20-40% hasil hortikultura rusak setelah panen. Hal ini menunjukkan diperlukan teknologi yang tepat dalam hal pemanenan dan penanganan pasca panen. Ruang lingkup penelitian dibatasi pada pembuatan buah olahan kering dengan cara pengeringan menggunakan pengering cabinet, vacuum dan fluidized bed. Pepaya diperoleh dari perkebunan IPB yang ada di daerah Ciomas, Bogor. Penelitian pendahuluan dimaksudkan untuk menentukan perlakuan awal buah sebelum proses pengeringan meliputi perendaman buah dalam larutan metabisulfit 1000 ppm dan 2000 ppm, pemilihan konsentrasi gula (10, 35, 45 "brix), pemberian asam askorbat dan asam sitrat serta besarnya irisan buah. Hasil terbaik yang diperoleh yaitu perlakuan sulfurisasi dengan cara perendaman dalam larutan meta-bisulfit dengan konsentrasi 2000 ppm selama 30 menit, asam sitrat, asam aksorbat 0,25% dan perendaman dengan gula 35" brix serta ukuran potongan buah setebal 2 cm. Untuk penelitian utama digunakan alat pengering cabinet, fluidized bed dan vacuum. Operasi pengeringan dilakukan pada suhu 65°C dan waktu pengeringan untuk cabinet 8-24 jam, fluidized bed 1-3 jam dan untuk vacuum 1-2 jam. Diperoleh hasil terbaik yaitu alat pengering yang digunakan adalah fluidized bed suhu 65°C, waktu pengeringan 2 jam dan kadar air produk 19,52%bb. Hasil terbaik dari penelitian ditentukan dari uji organoleptik dan analisa produk pepaya kering. Dari hasil kedua uji organoleptik diperoleh data bahwa panelis menyukai pepaya jenis IPB 1 mengkal yang dikeringkan dengan fluidized bed.
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