Judul: Penghitungan Sebaran Kerugian Agregat dengan Metode Monte Carlo.
Abstrak: Kerugian agregat adalah total kerugian yang dialami oleh pemegang polis yang harus ditanggung oleh suatu perusahaan. Sebaran kerugian agregat terdiri atas sebaran frequency dan sebaran severity. Sebaran frequency adalah sebaran banyaknya klaim, sedangkan sebaran severity adalah sebaran besarnya klaim. Dalam menghitung sebaran kerugian agregat dibutuhkan model sebaran compound. Sebaran kerugian agregat dapat dihitung dengan beberapa metode numerik, salah satunya dengan metode Monte Carlo. Penghitungan sebaran kerugian agregat dengan metode Monte Carlo dilakukan dengan proses simulasi untuk mendapatkan banyaknya klaim dan besarnya masing-masing klaim. Dari hasil simulasi tersebut, dilakukan penghitungan dua ukuran risiko, yaitu Value at Risk dan Expected Shortfall.
Keyword: Expected Shortfall, kerugian agregat, sebaran compound, simulasi Monte Carlo, Value at Risk

Judul: Penentuan Sebaran Kerugian Agregat Menggunakan Metode Fast Fourier Transform
Abstrak: Kerugian agregat adalah total kerugian yang dapat dihitung dengan pendekatan sebaran gabungan (compound distribution), baik secara analitik maupun numerik. Penentuan sebaran kerugian agregat dilakukan untuk memodelkan klasifikasi kerugian agregat yang meliputi penghitungan Value at Risk (VaR) dan Expected Shortfall (ES). Secara analitik, penentuan sebaran gabungan menggunakan metode fungsi karakteristik itu rumit. Sebagai alternatif, penentuan sebaran gabungan dihitung menggunakan metode fast Fourier transform. Dari data klaim dataCar di package R, diperoleh banyaknya klaim mempunyai sebaran Zero Truncated Negative Binomial (ZTNB) serta besarnya klaim mempunyai sebaran Inverse Gaussian (IG) dan sebaran Lognormal (LN). Sebaran compound ZTNB–IG lebih baik memodelkan besar VaR, nilai harapan, dan ragam data dibandingkan sebaran compound ZTNB–LN. Sedangkan untuk ES, kedua sebaran compound dapat digunakan untuk menghampiri ES empirik pada tingkat kepercayaan 97%., Aggregate loss is total losses that can be calculated with a compound distribution approach, both analytically and numerically. Determination of the aggregate loss distribution is carried out to model the classification of aggregate losses which includes the calculation of Value at Risk (VaR) and Expected Shortfall (ES). Analytically, the determination of the compound distribution using the characteristic function method is complicated. Alternatively, the determination of the compound distribution can be calculated using the fast Fourier transform method. From the dataCar claim data in package R, frequency claims have a Zero Truncated Negative Binomial (ZTNB) distribution and severity claims have an Inverse Gaussian (IG) distribution and a Lognormal (LN) distribution. The compound ZTNB–IG distribution better models the size of VaR, expectation value, and variance from the data compared to the compound ZTNB–LN distribution. Meanwhile for the ES, the two compound distributions can be used to approximate the empirical ES at the 97% confidence level.
Keyword: aggregate loss, characteristic function method, ES, fast Fourier transform method, VaR

Judul: Morphofunction changes of gonadal and mandibular glands of the cave swiflets (Collocalia linchi) during nesting and reproductive period
Abstrak: The present study aimed to study the morphological and histochemical changes and possible correlation between the gonads and mandibular glands of the cave swiflets (Collocalia linchi) during reproductive and nesting period. A total of seventy two adult birds were used in this study. The birds, three males and three females, were collected each month during a period of one year. After being sacrificed, samples of gonads and mandibular salivary glands were taken out and processed routinely for light microscopy. The present result showed that the gonads were active during the period of February - June. In the testis, the size of the testicle were similar throughout the year, but the testis had different color according to month. The testis in June - January were black in color, and were white and black in February, March, May and were all white in April. The size and structure of the ovaries were also increase towards February - May. Therefore the period of February - June was regarded as reproductive period of the cave swiftlet. The size and structure of mandibular glands were also clearly increased and the glands were more active during the nesting and reproductive period. Histochemically, the bindings of some lectins in the gonad and mandibular glands were also increase in the number of reactive cells and in the intensities of the positive reactions during the nesting and reproductive period, suggested that certain carbohydrates were involved and may play important roles in the reproductive function of the cave swiftlet. The present result showed that there were clear signs on the functional and structural changes of the gonads and mandibular glands of the cave swiftlets during the active nesting and reproductive period, suggested a possible regulatory mechanism of the mandibular gland through gonadal hormones pathway.
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