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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.
Rice Harvest Failure Risk Analysis Using Extreme Value Theory Based on Weather Index for Agricultural Business Supply Chain Management Riaman, Riaman; Sukono, Sukono; Supian, Sudradjat; Ismail, Noriszura
International Journal of Supply Chain Management Vol 9, No 5 (2020): International Journal of Supply Chain Management (IJSCM)
Publisher : ExcelingTech

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59160/ijscm.v9i5.5345

Abstract

This paper discusses the formulation of a risk model for paddy agricultural insurance in Indonesia. Indonesia as an agricultural country with a tropical climate, where the sun shines throughout its time, farmers can plant crops throughout the season. In particular, rice farming is currently an inseparable part of most agrarian societies in Indonesia, especially in West Java. However, changes in air temperature, weather and annual rainfall, which sometimes changes uncertainly, cause changes in cropping patterns. This weather uncertainty will certainly increase the risk of crop failure. This paper will analyze the effect of climate variables on the risk of crop failure. The climate variables in this analysis consist of temperature, wind speed, maximum temperature, minimum temperature, and rainfall. The method to be developed here is to use the parametric method which will be used as a reference to determine the magnitude of risk, namely generalized pareto distribution and peak over threshold as a threshold. The results obtained that the greatest risk of losses to farmers occurred in November, December, January, February and March with a value of 0.17485. The organization of this paper consists of introduction, methodology, results and discussion, and conclusions.