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Abstrak :
Analysis of various mistletoe grown on different host plants showed that the amount or value of mistletoe antioxidant activity, which were based on its ability to reduce K3Fe(CN)6 and Cerium (IV) Sulphate, were 0.092 - 2.403 mequiv and 0.103 - 3.309 mequiv for each gram of mistletoe. The ability of mistletoe samples to scavenge H202 were (1322 - 12.567 mmol for each gram of mistletoe. In general those three antioxidant methods showed the same order of activity, Dendrophthoe pentandra (L) Miq on tea as host plant gave the highest value, where Scurrula lepidota (G) Don on tea as host plant gave the smallest value. In general thin layer chromatogram profile with Rf 0.68; (180 and 0.91 are specific for all mistletoe genus examined. Dendrophthoe pentandra grown on tea has a big spot at Rf 0.80 when compared to other genus. Lepeostegeres gemmiflorus grown on tea has a big spot at Rf 0.51 but no spot at Rf 0.68. Scurrula lepidota grown on tea has the smallest spots at all Rf values when compared to other genus. Macroscopically mistletoe genus can be distinguished by its shape and size of stern, flowers and leaves. Microscopically Dendrophthoe and Lepeostegeres are specific for having astrosclereid while Scurrula and Macrosolen has stellate trichomes.

Abstrak :
ABSTRACT
Nitration of 3-(4-cblorophenyl)-2-metbyl-quinazolin-4-oneusing various nitration agents have been performed. The purpose of the experiment wa,;toget the best nitl'lltion agentsforthe synthesis of nitro derivative ofthe compomtd. The various nitration agentsused were:fuming nitric acid-concentrated sulfuric acid, silver nitrate-N-bromosuccinimide (NBS). eerie ammoniwn nitrate-silica supported sulfuric acid, and eerie ammonium ni􀃝ncentrated sulfuric acid. The results showed that nitrationwithfumingnitricacickoncentrated sulfuricacid obtained 3-( 4'-chloro-3 '-nitropheny l}-2- methyl-6-nitro--quinazolin-4-onein49. 74%yield. Thestructurewas confirmedusing FT-IRand1H-NMR The other nitration methods were not give the desired results.

Abstrak :
Categorical data is a kind of data that is used for computational in computer science. To obtain the information from categorical data input, it needs a clustering algorithm. There are so many clustering algorithms that are given by the researchers. One of the clustering algorithms for categorical data is k-modes. K-modes uses a simple matching approach. This simple matching approach uses similarity va-lues. In K-modes, the two similar objects have similarity value 1, and 0 if it is otherwise. Actually, in each attribute, there are some kinds of different attribute value and each kind of attribute value has different number. The similarity value 0 and 1 is not enough to represent the real semantic distance between a data object and a cluster. Thus in this paper, we generalize a k-modes algorithm for catego-rical data by adding the weight and diversity value of each attribute value to optimize categorical data clustering.

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Data Kategorial merupakan suatu jenis data perhitungan di ilmu komputer .Untuk mendapatkan infor-masi dari input data kategorial diperlukan algoritma klastering. Ada berbagai jenis algoritma klas-tering yang dikembangkan peneliti terdahulu. Salah satunya adalah K-modes. K-modes menggunakan pendekatan simple matching. Pendekatan simple matching ini menggunakan nilai similarity. Pada K-modes, jika dua objek data mirip, maka akan diberi nilai. Jika dua objek data tidak mirip, maka diberi nilai 0. Pada kenyataannya, tiap atribut data terdiri dari beberapa jenis nilai atribut dan tiap jenis nilai atribut terdiri dari jumlah yang berbeda. Nilai similarity 0 dan 1 kurang merepresentasi jarak antara sebuah objek data dan klaster secara nyata. Oleh karena itu, pada paper ini, kami mengembangkan algoritma K-modes untuk data kategorial dengan penambahan bobot dan nilai diversity pada setiap atribut untuk mengoptimalkan klastering data kategorial.