Judul: Literature Review on Caracteristic of Honey and Mint Leaf Extract as A Candidate of Functional Drink
Abstrak: Madu merupakan produk hasil ternak yang bermanfaat untuk menjaga kesehatan tubuh dan dapat diolah menjadi minuman fungsional. Penambahan ekstrak daun mint pada produk minuman fungsional madu dilakukan untuk memberi efek rasa dingin dan khasiat produk. Kajian pustaka ini bertujuan menganalisis karakteristik madu dan daun mint sebagai bahan baku produk minuman fungsional. Kajian pustaka dilakukan dengan penelusuran karya tulis ilmiah pada media dalam jaringan (daring). Hasil yang didapatkan berupa data sekunder mengenai karakteristik beberapa madu di Indonesia, jenis-jenis daun mint yang umum digunakan dalam produk pangan, senyawa bioaktif kedua bahan, metode ekstraksi senyawa bioaktif, dan pencampuran bahan sebagai minuman fungsional. Data kemudian dianalisis secara deskriptif. Madu-madu tropis yang lazim ditemui di Indonesia yaitu madu kaliandra, madu randu, madu kelengkeng, madu karet, dan madu rambutan potensial sebagai kandidat minuman fungsional dengan penambahan ekstrak daun mint dari spesies Mentha piperita, Mentha spicata, dan Mentha arvensis karena memenuhi ketentuan minuman fungsional berdasarkan karakteristik dan komponen bioaktif yang terdapat pada madu dan ekstrak daun mint., Honey is a livestock product that is useful for maintaining body health and can be processed into functional honey drinks. The addition of mint leaf extract to functional drink products is carried out to provide a cooling effect and product properties. This study aims to analyze the characteristics of honey and mint leaves as raw materials for functional drink products. Literature review is carried out by tracing scientific papers on online media. The results obtained were the form of secondary data about characteristics of honeys in Indonesia, types of mint leaves that are commonly used in food products, the bioactive compounds of the two ingredients, the extraction method for bioactive compounds, and the mixing of ingredients as functional drinks. The data were analysed using descriptive analysis. Tropical honey that is commonly found in Indonesia, namely calliandra honey, randu honey, longan honey, karet honey, and rambutan honey, are potential as a candidate for functional drinks with the addition of mint leaf extracts from the species Mentha piperita, Mentha spicata, and Mentha arvensis because they are fulfill the functional drink requirements based on the characteristics and bioactive components that found in honey and mint leaf extract.
Keyword: Bioactive compounds, functional drink, honey, mint lea

Judul: Characteristics of Physicochemical Properties, Antioxidants, and Organoleptic of Mixed Herbal Honey with the Addition of Curcuma (Curcuma xanthorrhiza) and Ginger (Zingiber officinale)
Abstrak: Salah satu pemanfaatan madu ialah dengan menambahkan atau mencampurkan herbal yang memiliki khasiat tertentu bagi kesehatan, antara lain untuk memelihara kesehatan, mengobati penyakit, dan perawatan tubuh. Campuran antara madu dan rempah-rempah disebut dengan madu herbal. Penelitian ini bertujuan untuk menganalisis sifat fisikokimia, antioksidan, dan organoleptik dari madu herbal, yaitu madu dengan penambahan temulawak (Curcuma xanthorrhiza) dan jahe (Zingiber officinale) yang diberikan penambahan serbuk 0%, 0,5%, dan 1% dari total volume madu dengan tiga pengulangan. Sifat fisikokimia yang dianalisis ialah warna, kadar air, kadar gula, kadar abu, nilai aw, pH, viskositas, dan aktivitas antioksidan. Hasil penelitian menunjukkan bahwa penambahan serbuk temulawak dan jahe terhadap madu berpengaruh meningkatkan kadar abu dan menurunkan viskositas. Penambahan serbuk temulawak dan jahe pada madu tidak berpengaruh terhadap kadar air, kadar gula, kapasitas air (aw), dan pH. Penambahan serbuk temulawak dan jahe pada madu tidak berpengaruh terhadap aktivitas dan kapasitas antioksidan. Hasil uji organoleptik oleh 32 panelis menunjukkan uji hedonik berpengaruh pada aroma, warna dan rasa, panelis lebih menyukai madu tanpa penambahan herbal. Karakteristik organoleptik mutu hedonik pada madu dengan penambahan serbuk temulawak dan jahe 1% lebih disukai panelis dalam hal rasa, kekentalan, dan aroma., One of the uses of honey is to add or mix herbs that have particular benefits for health, among others, to maintain health, treat disease, and take care of the body. The mixture of honey and spices is called herbal honey. This study aims to analyze the physicochemical, antioxidant, and organoleptic properties of herbal honey, namely honey with the addition of curcuma (Curcuma xanthorrhiza) and ginger (Zingiber officinale) given the addition of 0%, 0.5%, and 1% powder of the total volume of honey with three repetitions. The physicochemical properties analyzed were color, water content, sugar content, ash content, aw value, pH, viscosity, and antioxidant activity. The results showed that the addition of curcuma and ginger powder to honey affected increasing the ash content and decreased viscosity. Adding curcuma and ginger powder to honey did not affect water content, sugar content, water capacity (aw), and pH. The addition of curcuma and ginger powder to honey did not affect antioxidant activity and capacity. The results of organoleptic tests by 32 panelists showed that hedonic tests affected flavour, color, and taste, panelists prefer honey without the addition of herbs. The organoleptic characteristics of hedonic quality in honey with the addition of 1% curcuma and ginger powder were preferred by panelists in terms of taste, viscocity, and flavour.
Keyword: Antioksidan, Fisikokimia, Jahe, Madu Herbal, Temulawak

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