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All Journal International Journal of Global Operations Research International Journal of Quantitative Research and Modeling
Nurdyah, Himda Anataya
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Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Engineering Environmental Science Mathematics Physics

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Use of Constant Type Cost Prorate Method in Calculation of Actuarial Liability of Pension Funds Putrie, Veronica Clasrissa; Nurdyah, Himda Anataya
International Journal of Global Operations Research Vol. 5 No. 3 (2024): International Journal of Global Operations Research (IJGOR), August 2024
Publisher : iora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/ijgor.v5i3.321

Abstract

The purpose of this study is to calculate the actuarial liability value of pension funds using the Constant Percent type Cost Prorate method. This method is a pension funding method that calculates pension benefits based on the employee's salary since he first entered work. The method in this study is used to calculate the amount of actuarial liabilities that must be issued by the company to employees at the time of normal retirement, namely 58 years. The data used is the data of a Civil Servant of the Social Service in DKI Jakarta who is 55 years old. Normal contributions and actuarial liabilities that must be prepared by pension companies for pension plan participants increase as the age of pension plan participants increases. Based on the calculation results, the accumulated actuarial liabilities that must be prepared by the pension plan company in 2020 are IDR 3,843,981,410. 
Investment Portfolio Optimization Using the Mean-Variance Model Based on Holt-Winters Stock Price Forecasting of Food Sector in Indonesia Nurdyah, Himda Anataya; Subartini, Betty; Sukono, Sukono
International Journal of Quantitative Research and Modeling Vol 6, No 2 (2025)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v6i2.1017

Abstract

The importance of the food sector to Indonesia's economy makes it one of the most attractive sectors to consider in an investment portfolio. An optimal portfolio is the best choice for investors among various efficient portfolios, aiming to maximize returns while minimizing risk. Moreover, since investment is inherently associated with fluctuating stock prices, accurate forecasting is necessary to anticipate future stock movements. This study aims to accurately predict stock prices and construct an optimal portfolio consisting of five food sector stocks listed on the Indonesia Stock Exchange, namely DMND, ICBP, HOKI, INDF, and ULTJ. Stock price predictions are generated using the Holt-Winter method, which can identify seasonal patterns and trends from historical data. The predicted stock prices are then used to calculate returns, which serve as the basis for portfolio optimization using the Mean-Variance model. The results show that the Holt-Winter method successfully produces accurate stock price forecasts, with Mean Absolute Percentage Error (MAPE) values for all stocks below 10%. These forecasts are used to calculate returns in the portfolio optimization process. The optimal portfolio composition is determined with the following weight proportions: HOKI (4%), ICBP (18%), ULTJ (21%), DMND (26%), and INDF (30%). This portfolio yields an expected return of 0.0441% and a portfolio variance of 0.0063%, reflecting a balanced trade-off between potential return and risk.
Co-Authors Betty Subartini Putrie, Veronica Clasrissa Sukono .