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Noriszura Ismail
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Environmental Science Industrial & Manufacturing Engineering Mathematics Transportation

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Journal : Statistika

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Crisis Ability: Modified Ijarah Thumma Al-Bai’ vs. Rule 78 Nurfadhlina Binti Abdul Halim; Saiful Hafizah Jaaman@Sharman; Noriszura Ismail; Rokiah@Rozita Ahmad
STATISTIKA: Forum Teori dan Aplikasi Statistika Vol 10, No 2 (2010)
Publisher : Program Studi Statistika Unisba

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/jstat.v10i2.1016

Abstract

The intention of this paper is to investigate the ability of modified Ijarah Thumma Al-Bai’ (AITAB) model infacing the crisis compare with Rule 78 model. Both models are based on Shari’ah regulation for ijarahcontract and al-bai’ contract, but the modified AITAB model consideration is different from Rule 78. Inmodified AITAB modelling, we consider a partnership between lessor and lessee with musyarakahmutanaqisah concept being used, whereas in Rule 78 model such consideration does not exist. From theanalysis, we obtain a different result for IMAT and Rule 78 models, meaning both models are handlingthe crisis differently.
INSURANCE RISK CLASSIFICATION WITH NEGATIVE BINOMIAL DISTRIBUTION Noriszura Ismail; Abdul Aziz Jemain
STATISTIKA: Forum Teori dan Aplikasi Statistika Vol 4, No 2 (2004)
Publisher : Program Studi Statistika Unisba

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/jstat.v4i2.894

Abstract

Risk classification is the process of statistical modeling that classifies risks into cross-classified classes, characterized bythe rating factors. In this paper, risk classification is applied to estimate claim frequency rates, expressed in terms of claimcount per exposure unit. The Poisson regression model has been widely used to analyze claim frequency rates in the recentyears. However, under the Poisson model, the mean and variance is assumed to be equal within classes, i.e., homogeneousrates. In this paper, the Negative Binomial regression model is suggested to deal with heterogeneous rates. In addition, themeasures for goodness-of-fit of the model, namely the Pearson chi-square, deviance, and likelihood ratio test, are alsodiscussed. Finally, the procedure for estimation of parameters, namely the Iteratively Weighted Least Squares (IWLS), isalso shown. In this paper, the models are fitted and tested on two types of claim data; Canadian private automobile liabilityinsurance and Malaysian private automobile own damage insurance.
Pemodelan Klaim Asuransi Kendaraan Bermotor dengan Regresi ZAIG Yulia Resti; Noriszura Ismail; Saiful Hafizah Jaaman
STATISTIKA: Forum Teori dan Aplikasi Statistika Vol 10, No 2 (2010)
Publisher : Program Studi Statistika Unisba

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29313/jstat.v10i2.1018

Abstract

In motor insurance pricing based on risk of policyholder, modeling claim is the most important step.The modeling includes two main models there are model which relates to event of claims and modelthe cost of claims submitted to insurance companies. Most studies modeling the cost of claimsinvolving only the amount of claims which are positive, i.e. when an accident happens and then thepolicyholder filed a claim with the claims cost is greater than zero. In one period of insurance, there’repolicyholders who have not had an accident and there’re policyholders who had an accident but doesnot have claim, in this case is said to the claims cost is zero. This paper investigate theimplementation ZAIG (Zero Adjusted Inverse Gaussian) regression on the model of automobileinsurance claims that involve the cost of claims that zero and positive use data supported byInsurance Services Malaysia (ISM) Berhard. By regression ZAIG note that both the event and theaverage of claim cost significantly affected by the premium.
Co-Authors Abdul Aziz Jemain Nurfadhlina Binti Abdul Halim Riaman Riaman, Riaman Rokiah@Rozita Ahmad Saiful Hafizah Jaaman Saiful Hafizah Jaaman@Sharman Sukono Sukono Supian, Sudradjat Yulia Resti