Article Per Year (5 Year)
p-Index From 2020 - 2025
0.23
P-Index
This Author published in this journals
All Journal Statistika International Journal of Industrial Engineering, Technology & Operations Management
Saiful Hafizah Jaaman
Unknown Affiliation
Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Industrial & Manufacturing Engineering Mathematics

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
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.
Portfolio Optimization of Technology Companies in Malaysia: An Application of Fuzzy TOPSIS-Mean-Absolute Deviation Approach Siew, Lam Weng; Jaaman, Saiful Hafizah; Hoe, Lam Weng
International Journal of Industrial Engineering, Technology & Operations Management Vol. 1 No. 1 (2023): June 2023
Publisher : Indonesia Academia Research Society

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62157/ijietom.v1i1.18

Abstract

Selecting and weighting the companies are the main processes in portfolio optimization. It is important to select and determine the companies' weights in constructing the optimal portfolio. In this paper, we propose a two-phase Mean-Absolute Deviation (MAD) model in portfolio optimization of technology companies in Malaysia. In the first phase, the companies’ financial performance is determined and ranked with Fuzzy Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS). Selection of the good financial performance companies can minimize the influence of firm-specific risk in minimizing the risk of the portfolio at the expected return. In the second phase, the optimal portfolio is generated by weighting the selected companies with MAD model. The results indicate that the investors can minimize the portfolio risk to achieve the expected return with the two-phase MAD model. The significance of this paper is to contribute to the development of portfolio optimization by integrating the Fuzzy TOPSIS and MAD approaches.
Co-Authors Hoe, Lam Weng Noriszura Ismail Siew, Lam Weng Yulia Resti