Judul: Isolasi dan Identifikasi Bakteriosin Bakteri Asam  Laktat S12 dari Bekasam
Abstrak: Bakteri asam laktat penghasil bakteriosin diisolasi dari bekasam, makanan tradisional Indonesia dari Provinsi Lampung. Salah satu isolat yang menghasilkan bakteriosin potensial (isolat S12) teridentifikasi sebagai Lactobacillus plantarum S12 berdasarkan sekuen 16S rRNA. Analisis sekuen 16S rRNA menunjukkan homologi sebesar 98% dengan beberapa strain L. plantarum lainnya. Bakteriosin S12 (plantaricin S12) menunjukkan kemampuan menghambat beberapa patogen, terutama Listeria monocytogenes, dan Staphylococcus aureus. Plantaricin S12 yang dihasilkan berasosiasi dengan pola pertumbuhan yang dimulai pada fase awal eksponensial dan mencapai aktivitas maksimum pada fase awal stasioner. Plantaricin S12 cenderung stabil pada suhu tinggi hingga 121 °C selama 15 menit. Bobot molekul plantaricin S12 diperkirakan sekitar 10,79 kDa berdasarkan analisis SDS-PAGE. Selain itu, gen-gen yang menyandi plantaricin S12 diantaranya gen pln EF dan gen pln JK. Plantaricin S12 diperkirakan termasuk bakteriosin kelas II yang memiliki potensi untuk diaplikasikan sebagai biopreservatif pangan.
Keyword: Lactobacillus plantarum, plantaricin S12, SDS-PAGE analysis

Judul: Karakterisasi Bakteriosin Bakteri Asam Laktat Dari Sawi Fermentasi
Abstrak: Sawi asin merupakan produk sawi fermentasi asal Indonesia. Sejumlah galur bakteri asam laktat yang berasosiasi dengan makanan menghasilkan bakteriosin. Bakteriosin merupakan senyawa protein yang memiliki aktivitas bakterisida terhadap mikrob sekerabat. Bakteriosin dapat menghambat beberapa bakteri penyebab kerusakan pada pangan. Tujuan dari penelitian ini ialah mengisolasi bakteri asam laktat dari sawi fermentasi dan mengkarakterisasi bakteriosin yang dihasilkan serta potensinya menghambat pertumbuhan bakteri Staphylococcus aureus dan Escherichia coli. Isolat bakteri asam laktat pada media MRSA + CaCO3 0.5% ditunjukkan dengan adanya zona bening di sekitar koloni bakteri. Seleksi 66 isolat asam laktat menunjukkan 10 isolat dengan indeks penghambatan tertinggi terhadap bakteri S. aureus dan E. coli. Dua isolat dengan indeks penghambatan supernatan tertinggi dan berpotensi menghasilkan bakteriosin yaitu isolat PB3.6 dan PG1.9. Berdasarkan identifikasi molekuler, isolat PB3.6 menunjukkan kemiripan 96% dengan Lactobacillus plantarum JBE 160 dan isolat PG1.9 memiliki kemiripan 98% dengan Lactobacillus brevis KLAB12. Aktivitas tertinggi bakteriosin isolat PB3.6 diperoleh pada akhir fase logaritmik sedangkan aktivitas tertinggi bakteriosin isolat PG1.9 diperoleh pada fase stasioner. Aktivitas endapan tertinggi bakteriosin isolat PB3.6 terhadap bakteri S. aureus pada konsentrasi amonium sulfat 40% sedangkan terhadap bakteri E. coli pada konsentrasi amonium sulfat 80%. Bakteriosin isolat PG1.9 memiliki aktivitas endapan tertinggi terhadap bakteri S. aureus dan E. coli pada konsentrasi amonium sulfat 70%. Bakteriosin isolat PB3.6 dan PG1.9 masih aktif menghambat bakteri S. aureus dan E. coli setelah diberi perlakuan pH 4-10 selama 30 menit dan suhu 50-100°C selama 10 menit. Aktivitas optimum bakteriosin isolat PB3.6 dan PG1.9 terhadap bakteri E. coli pada pH 4. Bakteriosin isolat PB3.6 memiliki aktivitas optimum terhadap bakteri S. aureus pada pH 6 sedangkan bakteriosin PG1.9 pada pH 7. Hasil tersebut mengindikasikan bahwa kedua isolat tersebut dapat menghasilkan bakteriosin yang diharapkan dapat digunakan sebagai pengawet pada produk pangan.
Keyword: bakteri asam laktat, bakteriosin, sawi fermentasi, Lactobacillus plantarum, Lactobacillus brevis

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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