Judul: Penyebaran beberapa jenis cetacean subordo odontoceti di perairan laut Sawu bagian Timur, Nusa Tenggara Timur
Abstrak: Cetacean yang ditemukan di perairan Laut Sewu pada Tanggal 27-28 Desember 2005 terdiri atas 8 spesies dan 1669 ind dengan total 76 sighting. Panjang total transek adalah 400,22 km meliputi 400,22 km daerah pengamatan.
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Judul: Sebaran dan Tingkah Laku Cetacea Di Perairan Sekitar Taman Nasional Komodo, Flores, Nusa Tenggara Timur
Abstrak: Pada Bulan April 2003 diadakan penelitian mengenai sebaran dan tingkah laku Cetacea sebagai bagian dari proses monitoringCetacea yang rutin diadakan oleh The Nature Conservancy (TNC) bekerja sama dengan pihak Taman Nasional Komodo di perairan sekitar daerah Taman Nasional Komodo, Flores, Nusa Tenggara Timur. Penelitian ini menggunakan metode jelajah untuk mencari penampakan Cetacea dengan menggunakan metode pengamatan double-platform yang telah dimodifikasi. Penelitian ini bertujuan untuk mengetahui jenis-jenis, sebaran dan kelimpahan Cetacea terutama Sub ordo Odontoceti di perairan sekitar Taman Nasional Komodo serta mengetahui tingkah laku Cetacea di permukaan perairan pada habitat sebenarnya. Penelitian ini bersifat rapid assesment, menitikberatkan pada tiga daerah yaitu laut bagian utara Taman Nasional Komodo (Laut Flores); daerah selat (Selat Sape, Linta, Molo) dan pulau-pulau (Komodo, Rinca, Padar, Nusa Kode, Gili Banta, Sangeang) di sekitar wilayah Taman Nasional Komodo; dan laut bagian selatan Taman Nasional Komodo (Selat Sumba). Data yang diambil pada saat di lapangan adalah data tanggal dan waktu pada saat Cetacea tampak, posisi GPS, kondisi permukaan laut, nama spesies Cetacea yang tampak dan julT)lahnya, ada tidaknya bayi Cetacea, jarak dan arah Cetacea dari kapal, tingkah laku Cetacea yang tampak di permukaan perairan, dan spesies yang berasosiasi dengan Cetacea tersebut. Selanjutnya data-data tersebut diolah menggunakan software Microsoft Excel dan ARCVIEW. lndeks keadilan (evenness index) digunakan untuk melihat hubungan antara jumlah spesies Cetacea dengan kelimpahan individu. Selama enam hari survei terjadi 41 kali pertemuan dengan tujuh spesies Cetacea Sub ordo Odontoceti, satu genus dari Famili Delphinidae, dan satu Cetacea kecil yang teridentifikasi dengan jumlah total individu sebanyak 1228 individu. Dari hasil plot posisi koordinat GPS didapatkan hasil bahwa Cetacea Sub ordo Odontoceti yang terdapat di perairan Taman Nasional Komodo tidak merata penyebarannya. Laut Flores merupakan daerah yang paling banyak Cetaceanya (19 kali pertemuan) dengan total jumlah individu sebanyak 653 individu. Di daerah ini dijumpai enam spesies Cetacea dari Sub ordo Odontoceti yaitu Stenella longirostris (Spinner dolphin); Stenella attenuata (Spotted dolphin); Tursiops truncatus (Bottlenose dolphin); Pseudorca crassfdens (False Kiffer whale); Grampus griseus (Risso's dolphin.); Kogia simus (Dwarf Sperm whale); dan satu spesies yang tak teridentifikasi. Daerah selat (Selat Sape, Selat Linta, Selat Molo) dan pulau-pulau (Komodo, Padar, Rinca, Nusa Kode, Sangeang, Gili Banta, Nusa Kode, dan Gili Motang) terjadi sembilan kali pertemuan dengan total jumlah individu sebanyak 200 individu. Spesies yang dijumpai yaitu Stenella longirostris (Spinner dolphin); Stene/la attenuata (Spotted dolphin); Tursiops truncatus (Bottlenose dolphin). Se!at Sumba terjadl sebanyak 13 kali pertemuan dengan total jumlah individu sebanyak 375 individu. Jenis yang dijumpai yaitu Stenella longirostris (Spinner dolphin); Stenella attenuata ( Spotted dolphin); Sperm whale (Physeter macrocepha/us); dan satu genus yaitu Stene/la sp ….dst
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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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