Judul: Study of mealiness phenomena in apple (MAlus sylvestris Mill.) cultivar "Rome Beauty"
Abstrak: Masir adalah sifat organoleptik/inderawi yang hanya dapat dikenali dengan pengamatan menggunakan cicip, rabaan serta seringkali dapat terlihat oleh mata. Istilah masir mempunyai cakupan yang cukup luas, dan dinyatakan untuk banyak jenis komoditas seperti, salak, ubi jalar, singkong, kentang, apel, sawo dan bahkan untuk beberapa jenis makanan lain yang menyimpang seperti es krim, susu gula manis dan madu. Namun informasi tertulis mengenai kemasfran banyak diperoleh hanya dari umbi kentang. Informasi teknis tentang kemasiran buah-buahan termasuk apel, masih sangat terbatas, padahal kemasiran memegang peran penting dalam penanganan, perdagangan dan pengolahan buah-buahan dan umbi-umbian.
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Judul: Estimation of Physico-chemical Characteristics of Apple Fruit Using Near Infrared Spectroscopy
Abstrak: Apel (Malus sylvestris.) merupakan buah yang memiliki nilai ekonomi cukup tinggi di Indonesia. Apel banyak digemari oleh masyarakat Indonesia karena memiliki cita rasa yang khas dan menimbulkan efek segar pada orang yang mengonsumsinya. Cita rasa apel terbaik diperoleh ketika buah sudah matang sempurna dan apel merupakan buah klimaterik sehingga tingkat kematangan dipengaruhi oleh ketuaan buah saat dipanen. Namun penentuan ketuaan apel masih dilakukan secara visual tanpa alat bantu sehingga hasilnya kurang akurat, kurang objektif sehingga berpotensi kematangan tidak sempurna. Metode spektroskopi NIR (Near Infrared Spectroscopy) memberikan alternatif dalam menentukan tingkat ketuaan buah apel tanpa merusak bagian buah tersebut. Penelitian ini bertujuan untuk menduga sifat fisiko-kimia buah apel manalagi dengan tiga umur panen berbeda (130, 140, dan 150 hari setelah bunga mekar, HSBM) secara nondestruktif dengan menggunakan metode spektroskopi NIR. Sifat atau kandungan fisiko-kimia buah apel terkait dengan tingkat ketuaan buah apel. Parameter yang diuji untuk menentukan kandungan fisiko-kimia buah apel adalah total padatan terlarut, kekerasan daging, dan kadar air. Hasil penelitian menunjukkan hasil terbaik untuk pendugaan total padatan terlarut buah apel didapatkan menggunakan pra-pengolahan data Smoothing Savitzky-Golay (SGs) dengan nilai koefisien korelasi sebesar 0.93; standard error of calibration (SEC) sebesar 0.81 %brix; standard error of prediction (SEP) sebesar 0.86 %brix dan ratio of standard error of prediction to deviaton (RPD)sebesar 2.61. Untuk parameter kekerasan buah hasil terbaik didapatkan dengan pra-pengolahan data Multiplicative Scatter Correction (MSC) dengan nilai koefisien korelasi sebesar 0.78; SEC sebesar 0.47 N; SEP sebesar 0.45 N dan RPD sebesar 1.53. Untuk parameter kadar air didapatkan hasil terbaik dengan pra-pengolahan data Standard Normal Variate (SNV) dengan nilai koefisien korelasi sebesar 0.75; SEC sebesar 0.92%; SEP sebesar 0.85% dan RPD sebesar 1.50., Apple (Malus sylvestris.) is a fruit with high economic value in Indonesia. Apples are much favored by people in Indonesia because they have a distinctive taste and have a fresh effect on people who consume them. The best apple taste is obtained when the fruit is fully ripe and the apple is a climacteric fruit so that the level of maturity is influenced by the age of the fruit when it is harvested. However, the determination of the aging of apples is still done visually without any tools so that the results are less accurate, less objective so that the potential for ripeness is not perfect. The NIRS (Near Infrared spectroscopy) method provides an alternative to determine the level of maturity of apples without damaging the fruit. This study aims to estimate the physico-chemical properties of manalagi apples with three different harvest ages (130, 140, and 150 days after blooming, DAB) nondestructively by using the NIR spectroscopy method. The properties or physicochemical properties of apples are related to the level of maturity of apples. The parameters tested to determine the physico-chemical content of apples were total dissolved solids, flesh hardness, and moisture content. The results showed that the best results for estimating total soluble solids of apples were obtained using Smoothing Savitzky-Golay (SGs) data pre-processing with a correlation coefficient of 0.93; standard error of calibration (SEC) of 0.81 %brix; standard error of prediction (SEP) is 0.86 %brix and ratio
Keyword: Apple, flesh hardness, moisture content, NIRS, total dissolved solids

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