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All Journal Eksakta : Berkala Ilmiah Bidang MIPA International Journal of Global Operations Research
Riaman
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Agriculture, Biological Sciences & Forestry Astronomy Biochemistry, Genetics & Molecular Biology Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Energy Engineering Environmental Science Materials Science & Nanotechnology Mathematics Mechanical Engineering

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Analysis of Health Insurance Claims Factors using The Stochastic Restricted Maximum Likelihood Estimation (SRMLE) Binary Logistic Regression Model: (Case Study: Health Insurance Claims at XYZ Company in 2023) Bagariang, Elizabeth Irene; Riaman; Gusriani, Nurul
International Journal of Global Operations Research Vol. 6 No. 3 (2025): International Journal of Global Operations Research (IJGOR), August 2025
Publisher : iora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/ijgor.v6i3.389

Abstract

The health insurance claim approval process is a crucial aspect for insurance companies. Inaccuracy in predicting claim status can pose financial risks to the company and reduce policyholder trust. This study aims to identify the factors that influence the approval or rejection of health insurance claims. In this type of data analysis, the problem of multicollinearity among predictor variables is often encountered, which can lead to unstable parameter estimates. To address this issue, this study utilizes a binary logistic regression model with the Stochastic Restricted Maximum Likelihood Estimation (SRMLE) method, which is better suited to handle such conditions. The data used in this research includes the variables of total claim amount, premium price, number of insured individuals, employee age, and the number of previous claims recorded at XYZ Company. The results of the factor analysis, through the developed logistic regression model, show that the variables of total claim amount, premium price, and the number of insured individuals are significant factors influencing the probability of claim approval.
Quota Share Reinsurance and Excess of Loss Reinsurance Calculations Using Ruin's Theory Dwi Susanti; Riaman; Badrulfallah; Dimas Apriliyanto
EKSAKTA: Berkala Ilmiah Bidang MIPA Vol. 25 No. 03 (2024): Eksakta : Berkala Ilmiah Bidang MIPA (E-ISSN : 2549-7464)
Publisher : Faculty of Mathematics and Natural Sciences (FMIPA), Universitas Negeri Padang, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24036/eksakta/vol25-iss03/468

Abstract

Ruin theory is commonly used to predict the likelihood of bankruptcy for an insurance company and relates to the rate of surplus of the insurance company for the insurance policy portfolio. Considering the change in the insurance fund from time to time, the timing of the occurrence of a number of claims is highly taken into account. Ruin theory is necessary so that companies can anticipate and detect bankruptcy early. One way to help insurance companies minimize their bankruptcy chances is through reinsurance. In this paper, will discuss about application of ruin theory in computing two methods of reinsurance treaty, that is Quota Share Reinsurance and Excess of Loss Reinsurance to decide more effective method to minimize probability of ruin. Results show that Excess of Loss Reinsurance method more effective than Quota Share Reinsurance method to minimize ruin probability of insurance company.
Co-Authors Badrulfallah Bagariang, Elizabeth Irene Dimas Apriliyanto Dwi Susanti Nurul Gusriani, Nurul