Judul: Evaluasi Stabilitas dan Emotional Sensory Mapping Produk Teh dalam Kemasan PET.
Abstrak: Teh merupakan minuman yang populer dengan daya konsumsi yang tinggi. Peningkatan tren teh salah satunya disebabkan variasi penyajian dalam kemasan PET. Tingkat penetrasi pasar dan peluang bisnis yang tinggi telah mendorong banyak perusahaan untuk memproduksi teh dalam kemasan PET. Salah satu permasalahan yang dihadapi produsen adalah penurunan pH dan polifenol akibat suhu dan cahaya selama penyimpanan. Penurunan polifenol sampai di bawah standar mutu yang ada menyebabkan produk tidak dapat dipasarkan. Pemilihan konsumen terhadap suatu produk teh ditentukan oleh emosi yang dirasakan konsumen ketika mencicipi suatu produk tertentu. Salah satu faktor yang membentuk emosi adalah profil sensori yang terdapat pada suatu produk teh. Pemetaan profil sensori dan emosi dilakukan dengan metode CATA menggunakan panel konsumen dan perangkat lunak XLSTAT. Data yang dihasilkan disajikan dalam bentuk biplot antara profil sensori dan emosi untuk melihat kesukaan konsumen terhadap suatu produk teh.
Keyword: Teh, polifenol, pH, profil sensori, profil emosi, CATA

Judul: Profil Sensori dan Respon Emosi Produk Minuman Kopi Latte Komersial
Abstrak: Perkembangan pesat konsumsi kopi di Indonesia menjadikan banyaknya inovasi variasi, jenis pengolahan, dan jenis produk kopi bermunculan di pasaran. Salah satu yang digemari oleh masyarakat adalah minuman kopi dalam kemasan. Banyaknya produk kopi yang dipasarkan menjadikan adanya persaingan antar produsen sehingga perlu dilakukan perbaikan dan pengembangan kualitas produk agar dapat bersaing di pasaran. Proses perkembangan tersebut dapat dilakukan dengan memenuhi preferensi konsumen yang dipengaruhi oleh atribut sensori produk dan respon emosi yang muncul terhadap produk. Penelitian ini bertujuan mengetahui profil sensori minuman kopi latte dalam kemasan komersial menggunakan metode CATA (Check-All-That-Apply) dan respon emosinya dengan metode EsSense25. Digunakan 4 produk minuman kopi latte dalam kemasan komersial yang diujikan kepada 40 panelis konsumen. Data hasil pengujian kemudian diolah menggunakan XLSTAT. Berdasarkan hasil analisis, produk dengan kode 259 dianggap paling mirip profil sensorinya dengan produk ideal menurut preferensi konsumen. Atribut sensori yang masuk dalam kategori must have, liking, dan ideal, yaitu atribut sensori milky, caramel flavor, dan creamy dapat dijadikan atribut acuan untuk pengembangan produk. Seluruh produk yang diujikan memiliki respon emosi yang positif, di antaranya adventerous, calm, pleasant, active, dan interested., The rapid growth of coffee consumption in Indonesia has led to the emergence of numerous innovations in variety, processing methods, and coffee products in the market. One of the favored choices among consumers is packaged coffee beverages. However, the abundance of coffee products has intensified competition among manufacturers, prompting the need for continual improvement and quality development to stay competitive. This entails aligning with consumer preferences influenced by sensory attributes and emotional responses to products. This study aims to determine the sensory profile of commercially packaged latte coffee beverages using the CATA (Check-All-That-Apply) method and assess their emotional responses through the EsSense25 method. Fourty consumer panelists evaluated four commercially packaged latte coffee products, with the data analyzed using XLSTAT software. Results revealed that products with code 259 considered the closest in sensory profile to the ideal product according to consumer preferences. Key sensory attributes identified for product development are the attributes that belongs to must have, liking, and ideal, included milky, caramel flavor, dan creamy. All tested products elicited positive emotional responses, including adventerous, calm, pleasant, active, and interested.
Keyword: CATA, EsSense25, Packaged Latte Coffee Beverage, Sensory Attributes

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