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: Screening of Microbial Transglutaminase (MTGase) Enzymes from Actinomycetes Isolates of Makassar Strait
Abstrak: Enzim transglutaminase (TGase) merupakan enzim transferase dengan nama sistematik protein-glutamin-?-glutamiltransferase. Enzim TGase telah dilaporakan diproduksi oleh mikrob dan disebut Microbial Transglutaminase (MTGase). Actinomycetes merupakan mikrob penghasil senyawa aktif dalam jumlah yang sangat besar. Salah satu senyawa aktif yang dihasilkan Actinomycetes adalah enzim MTGase. Penelitian ini bertujuan menyeleksi Actinomycetes laut penghasil transglutaminase secara kualitatif serta memastikan keberadaan gen melalui amplifikasi dengan PCR. Metode penelitian meliputi seleksi isolat Actinomycetes menggunakan Filter Paper Disc, isolasi DNA, kuantifikasi DNA dan amplifikasi menggunakan PCR. Hasil penelitian menunjukkan 7 dari 46 isolat positif memiliki aktivitas transglutaminase dengan konsentrasi DNA tertinggi sebesar 125,45 ng/µl. Nilai kemurnian yang dibaca pada rasio A260/280 berada pada kisaran 1,83 – 1,92 dengan nilai rata-rata 1,88. Amplifikasi gen menggunakan primer PTgase-4 dan PTgase-5 menghasilkan pita berukuran 400 bp. Isolat Actinomycetes menunjukkan adanya aktivitas transglutaminase dan pemeriksaan amplifikasi diperoleh pita penyandi transgulaminase., Transglutaminase enzyme (TGase) is a transferase enzyme with the systematic name protein-glutamine-?-glutamyltransferase. TGase enzymes could be produced by microbes and it called Microbial Transglutaminase (MTGase). Actinomycetes is a microbe that produces a very large number of active compounds. One of the active compounds produced by Actinomycetes is the MTGase enzyme. This study aimed to qualitatively select marine Actinomycetes producing transglutaminase and ensure the presence of genes through amplification by PCR. The research method included selection of Actinomycetes isolates using Paper Disc Filter, DNA extraction, DNA quantification and amplification using PCR. The results showed that 7 out of 46 positive isolates had transglutaminase activity with the highest DNA concentration of 125.45 ng/µl. Purity values read on the A260/280 ratio were in the range of 1.83 - 1.92 with an average value of 1.88. Gene amplification using PTgase-4 and PTgase-5 primers produced a 400 bp band. Actinomycetes isolates showed transglutaminase activity and amplification examination obtained transgulaminase encoding band.
Keyword: amplifikasi, DNA, PCR, senyawa aktif, gen

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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