Judul: Screening of Microbial Transglutaminase (MTGase)-producing from Marine Actinobacteria Isolates from Flores Sea
Abstrak: Mikroba transglutaminase (MTGase) merupakan enzim yang banyak dimanfaatkan dalam industri pengolahan pangan karena memiliki keunggulan dibanding transglutaminase dari sumber lain. Salah satu mikroba yang potensial menghasilkan MTGase adalah Actinobacteria. Penapisan bakteri penghasil MTGase dari isolat Actinobacteria laut asal Laut Flores dilakukan untuk memperoleh isolat yang potensial menghasilkan MTGase. Penapisan Actinobacteria penghasil MTGase berdasarkan uji filter paper disk (FPD) yang dilanjutkan dengan penapisan gen pengkode transglutaminase dengan metode Polymerase Chain Reaction (PCR). Hasil positif dari uji FPD didapat dengan mengamati perubahan warna pada paper disk menjadi kecokelatan, dimana 10 dari 110 isolat positif MTGase. Uji PCR dilakukan dengan amplikasi gen pengkode MTGase dengan menggunakan primer forward PTGase4 dan primer reverse PTGase5. Hasil positif ditunjukkan dengan munculnya pita positif gen pengkode MTGase pada ~400bp, dimana dari 9 dari 10 isolat memiliki gen pengkode MTGase. Sekuens gen parsial TGase pada salah satu isolat Actinobacteria, yaitu MAF23-24 menunjukkan adanya domain konservasi transglutaminase dan sebagian besar basa nukleotida yang lestari pada gen TGase dari genbank.
Keyword: PCR, Actinobacteria Laut, FPD, Laut Flores, MTGase

Judul: Streptomyces Spp Penghasil Microbial Transglutaminase Dan Pengklonan Dna Penyandinya Melalui Konstruksi Pustaka Genom
Abstrak: Enzim transglutaminase (TGase, E.C. 2.3.2.13) merupakan enzim yang mengkatalisis reaksi perpindahan gugus asil antara residu glutamin (Gln) yang berfungsi sebagai donor asil dan residu lisin (Lys) sebagai aseptor yang membentuk ikatan silang (crosslinking) ε-(γ-glutamyl) lisin isopeptida yang menghasilkan ikatan kovalen inter atau intramolekuler yang berikatan silang dengan protein makanan. Produksi enzim Microbial Transglutaminase (MTGase) dari strain liar mempunyai beberapa kelemahan yaitu selain pertumbuhan selnya lambat, produk yang dihasilkan sedikit dan protein yang dihasilkan juga bercampur dengan protein lainnya. Selain itu proses pemurnian cukup sulit karena memerlukan beberapa tahap pemurnian. Pendekatan teknologi rekayasa genetika sangat diperlukan untuk mendapatkan hasil yang lebih baik sehingga dapat dikembangkan dalam skala industri. Penelitian ini bertujuan untuk mendapatkan bakteri yang menghasilkan MTGase dan mengklon fragmen DNA penyandinya. Untuk itu, penelitian ini dilakukan melalui beberapa tahapan yaitu, penapisan bakteri Streptomyces spp penghasil MTGase, identifikasi isolat penghasil MTGase dan pembuatan pustaka genom dengan mengkloning fragmen DNA 40 kb yang mengandung gen penyandi MTGase. Hasil penelitian menunjukkan bahwa penapisan terhadap bakteri Streptomyces spp penghasil MTGase yang diisolasi dari berbagai jenis tanah di Indonesia, mendapatkan satu isolat yang potensial yaitu TTA 02 SDS 14. Analisis molekuler dengan PCR membuktikan bahwa isolat tersebut mengandung gen MTGase. Sekuen parsial gen MTGase dari isolat tersebut memiliki homologi 93 % dengan MTGase dari Streptomyces cinnamoneus. Berdasarkan sekuen gen 16S rRNA, isolat TTA 02 SDS 14 memiliki kekerabatan terdekat dengan Streptomyces thioleteus dengan homologi 99%. Pustaka genom dengan sisipan fragmen ~40 Kb yang membawa gen MTGase telah berhasil dikonstruksi dengan menggunakan fosmid pCC1FOSTM di dalam E.coli EPI300-TIR.
Keyword: MTGase gene, Streptomyces spp, Pustaka Genom

Judul: The Effects of Variance of Interest rate to Variance of Annuity Future Values
Abstrak: Time value of money is a concept that refers to the difference of the value of money due to time difference. The value of money for present time would not be the same as the value of money in the future. The value of money for present time is called as Present Value (PV) of the money and the value of money for future time is called Future Value (FV) of the money. Determination the value of money, for present and future time, depends on the time and rate of return. The value of money is determined by several factors such as inflation, fluctuation of interest rates, and government policy in securities and taxation. Due to fluctuation of the value of money we need a FV formulation, it is useful for knowing whether an investment can be profitable or not, and this information is useful also in budget analysis. Annuity is defined as a series of payments made for a specific period. The payment, fixed or varied, can be made at the beginning or at the end of the period. Annuity paid at the beginning of the period is called annuity-due and annuity paid at the end of the period is called immediate annuity-certain. The accumulated value of the annuity after few years later is called as a final value or a future value. Burnecki et al. (2003) have discussed about the FV of a fixed-rate annuity in which payments are made according to the arithmetic or geometric series. They have also examined FV for annuities in which payments are made according to arithmetic or geometric series with random rates of interest. This paper examines FV for annuity-due in which payments are made according to arithmetic or geometric series with interest rates as a random variable, which is normal distribution ,  . Future value formula is expressed in recursive form. FV for annuity-due which payments are made according to the arithmetic or geometric series with random rates of interest is calculated by theoretical way and simulation way. The random rates of interest is denoted as k k i  i  , where k i an independent random variable; i is a constant and k  is a random variable which has normal distribution ,  . By using the determined parameters, a sequence of random rates of interest are generated for theoretical calculation. Meanwhile for the simulation, the random rates of interest is generated 1000 times for the simulation. The generated data give mean value, variance, and standard deviation. Moreover, error of mean value, variance, and standard deviation from the theoretical and simulation results are calculated. Error calculation uses Symmetric Mean Absolute Percentage Error (SMAPE). The smaller the value of SMAPE is the more accurate the simulation. The interest rate variances are varied from 0.000036 to 0.0001 to study the relationship between variance of rates of interest and variance of future value. The theoretical and simulation results show that when the variance of random rates of interest increases, then the variance of FV increases linearly. FV of the annuity-due in
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