Operational risk is defined as the risk of loss resulting from inadequate or failed internal processes or external problems. Insurance companies as financial institution that also faced at risk. Recording of operating losses in insurance companies, were not properly conducted so that the impact on the limited data for operational losses. In this work, the data of operational loss observed from the payment of the claim. In general, the number of insurance claims can be modelled using the Poisson distribution, where the expected value of the claims is similar with variance, while the negative binomial distribution, the expected value was bound to be less than the variance.Analysis tools are used in the measurement of the potential loss is the loss distribution approach with the aggregate method. In the aggregate method, loss data grouped in a frequency distribution and severity distribution. After doing 10.000 times simulation are resulted total loss of claim value, which is total from individual claim every simulation. Then from the result was set the value of potential loss (OpVar) at a certain level confidence.
The capital market is a place for someone to invest in financial assets, one of which is equity instruments (stocks). Investment activities are very useful to get the maximum return, but with appropriate and acceptable risk. Stocks in this study are divided into defensive and aggressive stocks which are classified according to the level of risk. This risk must be considered by investors before investing. The parameter associated with systematic risk is called beta. The objects of research in this paper are 20 stocks consisting of ANTM, BBCA, BKSL, CPIN, GGRM, ICBP, KLBF, TLKM, PTBA, UNVR, ADHI, ADRO, AKRA, ASII, BBKP, BRPT, BMRI, CTRA, EXCL, and WIKA. The research method used is regression analysis to determine the beta value of stocks to be classified as defensive or aggressive stocks. At the end of the study, the effect of stock beta on return has an effect of 61.9%. While the other 38.1% are influenced by factors outside the independent variables.
Analisis survival merupakan analisis yang digunakan untuk menganalisis data kelangsungan waktu hidup (survival time). Waktu survival (survival time) merupakan salah satu penelitian yang digunakan untuk menghitung waktu dari munculnya gejala sampai dengan munculnya kejadian. Dalam analisis survival dikenal istilah data survival yaitu data yang menunjukkan waktu suatu individu dapat bertahan hingga terjadinya suatu kejadian. Penelitian ini akan membahas perbandingan estimasi parameter model survival berdistribusi Rayleigh dengan Metode Bayesian SELF menggunakan prior Vague dan Uniform. Proses estimasi parameter memerlukan informasi dari fungsi likelihood dan distribusi prior yang kemudian akan membentuk distribusi posterior. Setelah diperoleh estimator pada metode Bayesian SELF, selanjutnya diterapkan pada data program transplantasi jantung yang dilakukan Stanford dari Oktober 1967 sampai Februari 1980. Berdasarkan dari nilai MSE pada penelitian ini, diperoleh metode Bayesian SELF dengan prior vague lebih baik dari metode Bayesian SELF dengan Prior uniform.
Background: Heme oxygenase-1 (HO-1) is a protein secreted by immune cells as a part of immune response mechanism.HO-1 can be induced by variety agents that causingoxidative stress, such as exposure to 100% oxygenat2,4 ATA pressure.It plays a vital role in maintaining cellular homeostasis.This study was conducted to identify the effect of hyperbaric oxygen exposure in cultured ofPBMCthat infected by HIV-1. Material and Methods: Primary culture of PBMCs were isolated from 16 healthy volunteers and HIV-1 infected MT4 cell line by co-culture. The PBMCs were aliquoted into two wells as control group and treatment group. The 16 samples of HIV-1 infected PBMCwere exposed to oxygen at 2,4 ATA in animal hyperbaric chamber forthree times in 30 minutes periods with 5 minutes spacing period, that called 1 session. The Treatment done on 5 sessions within 5 days. 16 samples of HIV-1 infected PMBCs that have no hyperbaric treatment became control group.The supernatant were measured the HO-1 production by ELISA andmRNA expression of HO-1 by real time PCR and the number ofantigen p24 HIV-1by ELISA. Results: The result showed that there was no increasing of HO-1 at both mRNA level and protein level, there was a decreasing number of antigen p24 HIV-1 at the treatment group. In addition, hyperbaric exposure could not increase the expression of HO-1, more over the viral replication might be reduced by other mechanism. Conclusions: Hyperbaric oxygen could increases cellular adaptive response of PBMCs infected HIV-1 through increased expression of proteins that can inhibit HIV viralreplication.
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