Judul: Food Pairing Sensory Evaluation of Complimentary Food for Consuming Tea
Abstrak: Food pairing adalah metode ilmiah untuk mengidentifikasi makanan dan minuman mana yang cocok dikombinasikan. Penelitian secara formal mengenai food pairing di Indonesia belum dilakukan, termasuk mengenai makanan yang paling cocok jika dipadukan dengan teh sebagai minumannya. Maka dari itu, penelitian ini bertujuan meneliti mengenai food pairing, menganalisis makanan yang paling cocok sebagai pendamping minum teh, dan mengidentifikasi profil sensorinya menggunakan panelis konsumen berbasis home use test. Penelitian dilakukan dengan tahapan antara lain survei online mengenai pola konsumsi teh dan screening makanan pendamping teh yang paling diminati, kemudian dilakukan focus group discussion (FGD) untuk menentukan atribut sensori yang diujikan, dan uji sensori menggunakan metode check-all-that-apply (CATA). Hasil survey menunjukkan masyarakat menyukai teh hitam manis hangat yang dipadukan dengan biskuit. Berdasarkan analisis CATA, atribut yang diinginkan konsumen pada perpaduan yang ideal adalah buttery, creamy, gurih kelapa, sandy, dan manis. Pasangan produk yang paling mendekati ideal adalah teh dengan biskuit Roma Kelapa yang perpaduanya dapat meningkatkan rasa manis, meningkatkan mouthfeel buttery dan creamy, serta menurunkan tekstur sandy., Food pairing is a research method for identifying the suitability of certain foods and drinks for each other. No food pairing research has been conducted in Indonesia, including concerning the most appropriate food when combined with tea. Thus, this study will investigate how many different food items can be combined with tea and the characteristics of those food items. The research was carried out by stages, including an online survey of tea consumption patterns, a screening of most popular tea companion food products, a focus group discussion to determine the sensory attributes tested, and sensory tests using the check-all-that-apply (CATA) method. The survey respondents liked the combination of tea and biscuits. Based on CATA calculation. The qualities consumers seek when purchasing buttery, creamy, coconut flavored biscuits are buttery, creamy, coconut taste, sandy, and sweet. The closest product pair to the ideal is tea with Roma Kelapa. This combination will increase sweetness, increase rich mouthfeel, and reduce the sandy texture.
Keyword: CATA, food pairing, tea

Judul: Perspektif Konsumen Pada Food Pairing Less Sugar Tea Ready to Drink Dan Makanan Pendamping Dengan Metode Check All That Apply (CATA) di Kabupaten Situbondo
Abstrak: Teh merupakan produk minuman yang paling banyak beredar dalam kemasan siap minum (ready to drink). Less sugar tea ready to drink merupakan teh kemasan dengan klaim rendah gula siap saji dan siap dikonsumsi, less sugar tea ready to drink dapat juga dikonsumsi dengan berbagai makanan pendamping. Perpaduan pasangan makanan dan minuman seperti less sugar tea RTD dengan makanan pendampingnya akan menghasilkan sifat sensori jika dikonsumsi secara bersamaan yang disebut juga food pairing. Penelitian ini bertujuan untuk mengidentifikasi karakteristik atribut sensori, emosi, dan needstate dari perpaduan less sugar tea RTD dengan makanan pendampingnya. Penelitian ini dulakukan tahapan awal panelis, Focus Group Discussion (FGD) untuk menentukan atribut sensori, emosi, dan needstate, dan pengujian sensori yang dilakukan secara Home Used Test (HUT). Respon yang didapatkan diolah menggunakan Software XLSTAT dan menghasilkan profil sensori, emosi, dan needstate food pairing less sugar tea RTD. Hasil pengujian menunjukkan konsumen menyukai less sugar tea RTD dipasangkan dengan makanan ringan keripik singkong. Profil “less sugar tea RTD-keripik singkong” didominasi oleh atribut sensori floral aroma, roasted aroma, tea flavor, sweet, astringent, roasted beef aroma, cassava flavor, crunchy, umamy, mouthfeel oily, salty aftertaste, dan bitter afterstate sehingga mendekati pasangan ideal berdasarkan hasil CATA, pasangan ini juga menghasilkan emosi positif seperti satisfied, adventoures, dan energetic saat mengkonsumsinya. Profil less sugar tea RTD dengan makanan pendamping crackers didominasi oleh atribut floral aroma, roasted aroma, tea flavor, sweet, astringent, milky aroma, cheese flavor, crunchy, salty, mouthfeel creamy, salty aftertaste, dan bitter afterstate. Sedangkan emosi negatif muncul ketika mengonsumsi less sugar tea dengan makanan pendamping, biskuit dan creackers yaitu emosi negatif flat, bored, dan dissapointed. Intensitas setiap atribut pada ketiga pasangan sampel mengalami perubahan yaitumeningkat, tetap, atau menurun saat dipasangkan. Pasangan “less sugar tea RTD- Keripik singkong” dinilai memiliki kompleksitas overall flavor yang menghasilkan harmoni yang baik dibandingkan pasangan lainnya. Berdasarkan keseluruhan data yang diperoleh, pasangan “less sugar tea RTD- Keripik singkong” merupakan pasangan terbaik menurt panelis konsumen., Ready-to-drink (RTD) tea is packaged tea that widely available in supermarkets, one of its product is less sugar tea. Less sugar tea RTD had low sugar claims, ready to serve-consume, and was also be consumed with various complementary foods. The combination of less-sugar tea RTD with complementary foods will produce sensory properties if consumed simultaneously, as called food pairing. This study aimed to identify the characteristics of sensory, emotional, and need-state attributes of the combination of less sugar tea RTD and its complementary food. This research was conducted by initial panelist screening, Focus Group Discussion (FGD) to determine sensory atributes, emotions, and need-state, sensory testing conducted by Home Used Test (HUT). The responses obtained were processed using XLSTAT Software and produced a sensory profile, emotions, and needstate food pairing less sugar tea RTD. The results showed that consumers like less sugar tea RTD paired with cassava chips snacks, with sensory attributes i.e., floral aroma, roasted aroma, tea flavor, sweet, astringent, roasted beef aroma, cassava flavor, crunchy, umamy, oily mouthfeel, salty aftertaste, and bitter. It’s close to the ideal pairing based on CATA results. This pairing also produces positive emotions (satisfied, adventurous, and energetic) for consumer. While less sugar
Keyword: Less sugar tea, Home Used Test, Food Pairing, Check All That Apply (CATA)

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