Judul: Ekstrak Kasar Biopigmen Bakteri Laut yang Memiliki Aktivitas Antibakteri dan Antioksidan serta Identifikasi Senyawa Kimianya
Abstrak: Metabolit sekunder yang dihasilkan oleh bakteri laut asosiasi spons sangat beragam, salah satunya adalah biopigmen. Biopigmen bakteri memiliki berbagai potensi dalam bidang farmakologis seperti antibakteri, antifungi, dan antioksidan. Penelitian ini bertujuan menganalisis aktivitas antibakteri dan antioksidan ekstrak biopigmen dari isolat SAB E-64 dan P1.S9, mengidentifikasi kandungan kimianya, serta mengidentifikasi jenis isolat bakteri tersebut melalui pendekatan molekuler. Uji aktivitas antibakteri menunjukkan ekstrak biopigmen SAB E-64 paling baik menghambat pertumbuhan Staphylococcus aureus sedangkan biopigmen isolat P1.S9 paling baik menghambat pertumbuhan Bacillus subtilis. Hasil uji toksisitas berupa nilai LC50, 144,62 µg/ml untuk SAB E-64 dan 122,15 µg/ml untuk P1.S9 menggunakan metode Brine Shrimp Lethality Test (BSLT). Uji aktivitas antioksidan biopigmen menunjukkan nilai IC50 sebesar 238,25 µg/ml untuk biopigmen SAB E-64 serta 164,05 µg/ml untuk biopigmen P1.S9. Analisis senyawa kimia dengan GC-MS menunjukkan bahwa komponen yang mendominasi ekstrak biopigmen SAB E-64 adalah golongan alkana sedangkan P1.S9 didominasi oleh asam lemak. Analisis gen 16S-rRNA menunjukkan bahwa SAB E-64 memiliki kesamaan terdekat dengan Kocuria marina dan P1.S9 dengan Pseudomonas aeruginosa.
Keyword: bakteri laut, biopigmen, antibakteri, antioksidan, senyawa kimia.

Judul: Antimicrobial, Antioxidant, and Toxicity Activity of Marine Actinomycetes Biopigment Extract
Abstrak: Aktinomiset merupakan bakteri Gram-positif yang mempunyai potensi sebagai sumber metabolit sekunder baru. Salah satu metabolit sekunder tersebut adalah biopigmen. Biopigmen yang dihasilkan oleh aktinomiset mempunyai berbagai aktivitas biologis. Penelitian ini bertujuan menguji kemampuan antimikrob, antioksidan, dan toksisitas ekstrak biopigmen aktinomiset laut kode HV11.P3 dan SCA54.P2. Aktivitas antimikrob diuji terhadap beberapa mikrob patogen dan menunjukkan hasil terbaik dalam menghambat pertumbuhan Bacillus subtilis ATCC 19659 untuk ekstrak HV11.P3 kemudian Escherichia coli ATCC 8739 untuk SCA54.P2.Aktivitas antioksidan terhadap radikal DPPH menunjukkan nilai IC50 231,084 μg/ml untuk HV11.P3 dan 369,296 μg/ml untuk SCA54.P2. Hasil uji toksisitas berupa nilai LC50 yaitu 94,603 μg/ml untuk HV11.P3 dan 131,220 μg/ml untuk SCA54.P2 menggunakan metode Brine Shrimp Lethality Test (BSLT). Senyawa kimia penyusun ekstrak diidentifikasi menggunakan GC-MS. Hasilnya senyawa 1H-Purine-2,6-dione, 3,7-dihydro-1,3,7-trimethyl- (CAS) menjadi penyusun dominan ekstrak HV11.P3 dengan peak area 44,65% dan 5-Methoxypyrrolidin-2-one dengan luas peak area 30,23% untuk ekstrak biopigmen SCA54.P2. Analisis gen 16S rRNA menunjukkan bahwa HV11.P3 memiliki kesamaan terdekat dengan Micromonospora chalcea strain 1464-217L dan SCA54.P2 dengan Micromonospora tulbaghiae strain TVU1., Actinomycetes are Gram-positive bacteria that have potency as a source of new secondary metabolites. One of those secondary metabolites is biopigments. Biopigments produced by actinomycetes have various biological activities. This study aimed to determine antimicrobial, antioxidant, and toxicity activity from marine actinomycetes biopigment extract coded as HV11.P3 and SCA54.P2. Antimicrobial activities were tested against several pathogenic bacteria and showed the best result for inhibiting Bacillus subtilis ATCC 19659 for HV11.P3 and Escherichia coliATCC 8739 for SCA54.P2. The antioxidant activity against DPPH radical showed IC50 value 231,084 μg/ ml for HV11.P3 and 369,296 μg/ ml for SCA54.P2. The toxicity test results (LC50) based on Brine Shrimp Lethality Test (BSLT) were 94,603 μg/ ml and 131,220 μg/ ml for HV11.P3 and SCA54.P2, respectively. The major chemical compounds of HV11.P3 extract were identified as 1H-Purine-2,6-dione, 3,7-dihydro-1,3,7-trimethyl- (CAS) (peak area 44,65%) and 5-Methoxypyrrolidin-2-one for SCA54.P2 (peak area 30,23%). The 16S rRNA gene analysis showed that HV11.P3 had the closest similarity with Micromonospora chalcea strain 1464-217L and SCA54.P2 with Micromonospora tulbaghiae strain TVU1.
Keyword: BSLT, DPPH, Extract, GC-MS, 16S rRNA gene

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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