Judul: Sistem Bonus Malus dengan Frekuensi Klaim Berdistribusi Geometrik dan Ukuran Klaim Berdistribusi Weibull
Abstrak: Bonus-Malus system is one of systems implemented by an insurance in calculating the risk premium based on claim history from each policyholder. In this work we discussed two different types of Bonus-Malus system namely the classical Bonus-Malus system and the optimal Bonus-Malus systems. The classical Bonus-Malus system sets the risk premium by taking into account only the number of accidents of each policyholder. While the optimal Bonus-Malus system sets the risk premium by taking into account both the frequency and the severity of the claims of each policyholder. Both of the Bonus-Malus systems are then compared, with the number and size of the claims and insured persons are assumed to follow respectively a geometric and a Weibull distributions. The risks faced by each policyholder are different such that the number and size of the claims experienced by each policyholder are also different. Fu r t h e rmo r e , posterior distribution o f severity and frequency claim parameters is estimated by using Bayes method. Subsequently, solutions of both systems are obtained in term of future premium based on claim history from each policyholder.
Keyword: Bogor Agricultural University, Weibull distribution., geometric distribution, Bonus-Malus systems

Judul: Sistem Bonus-Malus dengan Banyak Klaim Berdistribusi Geometrik dan Besar Kerugian Berdistribusi Weibull Terpotong
Abstrak: Insurance is one way to denigrate financial loss by channeling the risk of loss of the person to another entity, for example automobile insurance. The risk premium of the automobile insurance is determined by insurance that is known data in the past (experience rating). System experience rating could call as Bonus-Malus system. In the Bonus-Malus system, policyholders who has submitted one or more claims will be subjected to a risk premium increase (malus), whereas for policyholders who did not file a claim would be rewarded with a decrease in risk premium (bonus) in the next premium payment period. Bonus-Malus system is said to be optimal if it is financially balanced for insurance companies and fair for policyholders. That is, the determination of the risk premium is not only based on the claims frequency but also based on the severity. In this study, we used the Bonus-Malus system by Mert and Saykan (2005) and Ni et al. (2014). But, previous research concern with the determination of the risk premium Bonus-Malus system which is applied to all of the severity that guaranteed by the insurance company. In fact, all of the severity proposed by policyholder could not be covered by insurance company. When an insurance company sets a maximum bound of the severity incurred, it is necessary to modify the model of the severity distribution into the truncated severity distribution. The claim frequency is geometric distribution as a combination of Poisson and exponential distribution. While, the severity distribution by Ni et al. (2014) modified to be the severity distribution with maximum bound is truncated Weibull distribution. Truncated Weibull distribution is a combination of truncated exponential and Levy distribution. In this study, we also compared the risk premium between the full severity and the severity with the maximum bound. The result shows that the risk premium equation with maximum bound is           3 2 t 1 1 2 1 2 Premium K K B c N u K n K N u K n  t c B c N u K n                                 , where 𝐾 is the total claim frequency, 𝑢 is the maximum bound that covered by insurance company, 𝑁 is the total severity which is lower than bound 𝑢, 𝑛 is the claim frequency which is lower than bound 𝑢, 𝐵𝐾−1/2 is the Bessel function with index 𝐾 − 1/2, 𝜃 is the parameter of the claim frequency distribution, and 𝑐 is the parameter of the severity distribution. The risk premium equation for the next period shows that the risk premium depends on the claim frequency, time period, and the total severity. The risk premium of Bonus-Malus system with the severity component based on Weibull distribution is equal to the risk premium based on truncated Weibull distribution when the severity component are less than the maximum bound of severity. Whereas, the
Keyword: truncated Weibull distribution, Weibull distribution, geometric distribution, Levy distribution, Bonus-Malus system, experience rating, the risk premium

Judul: Pemurnian dan karakterisasi protein inhibitor RNA helikase virus hepatitis C
Abstrak: Hepatitis C virus (HCV) infection is the second most common chronic viral infection in the world with global prevalence. This infection is contribution to chronic hepatitis and liver cirrhosis, often leading to hepatocellular carcinoma. There is no effective drug and vaccine available against HCV. The current standard treatment, a combination of pegylated interferon-α with ribavirin, is limited by its suboptimal response rate in a significant patient population, side effects, and affordability. Therefore, development of effective drug is needed. One approach to find out the candidate of antiviral drug is to discover the inhibitor of enzyme that essential for virus replication, such as RNA helicase. Streptomyces chartreusis 5-095 produce the inhibitor of HCV RNA helicase. The aim of this study was to purify the protein inhibitor which has inhibition activity against ATPase activity of RNA helicase HCV from S. chartreusis 5-095. The supernatant of culture S. chartreusis 5-095 exhibited high inhibiton activity against ATPase activity of RNA helicase HCV (approximately 72%) at 10 days of incubation. The extracellular protein inhibitor was partially purified by procedures of precipitation with ammonium sulfate to 65% saturation and gel filtration (Sephadex G50) using methanol water solution (4:6) as an eluen. The purity of protein inhibitor was monitored by SDS PAGE. The protein inhibitor showed a relative molecular mass were estimated to be 14 kDa and increased the purity 23,08 fold than those of the crude protein. The specific activity and IC50 after purification were 13,1338 U/mg and 0,0767 mg/mL, respectively. The activity of purified protein inhibitor showed its stability over pH range from 5-8 and optimum at pH 7,4. The inhibition activity showed its stability up to 70% at temperature 100 oC. The purified protein inhibitor relatively stable its activity at storage in the range of -20 oC to room temperature for 35 days.
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