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All Journal CAUCHY: Jurnal Matematika Murni dan Aplikasi Kubik Jurnal Matematika: MANTIK Teorema: Teori dan Riset Matematika International Journal of Supply Chain Management Eksakta : Berkala Ilmiah Bidang MIPA FIBONACCI: Jurnal Pendidikan Matematika dan Matematika Kumawula: Jurnal Pengabdian Kepada Masyarakat BERNAS: Jurnal Pengabdian Kepada Masyarakat Jurnal Lebesgue : Jurnal Ilmiah Pendidikan Matematika, Matematika dan Statistika KUBIK: Jurnal Publikasi Ilmiah Matematika International Journal of Business, Economics, and Social Development Operations Research: International Conference Series International Journal of Global Operations Research International Journal of Quantitative Research and Modeling Jurnal Matematika Integratif In Search (Informatic, Science, Entrepreneur, Applied Art, Research, Humanism) Mathematical Sciences and Applications Journal
Betty Subartini
Departemen Matematika, FMIPA, Universitas Padjadjaran
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Actuarial Calculation of Pension Funds Using Attained Age Normal (AAN) at PT Taspen Cirebon Branch Office: For Normal Pension Amalia, Hana Safrina; Subartini, Betty; sukono, sukono
Operations Research: International Conference Series Vol. 5 No. 3 (2024): Operations Research International Conference Series (ORICS), September 2024
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v5i3.332

Abstract

The pension program for Civil Servants (PNS) in Indonesia is managed by PT Taspen (Persero), which is responsible for ensuring the welfare of employees after retirement. One of the important components in the management of this pension fund is the actuarial calculation, which serves to determine the amount of normal contributions that must be paid by participants and the actuarial obligations that are the company's dependents. This calculation uses the right actuarial method to maintain the financial stability of the company and ensure that pension benefits can be optimally provided to participants. This study focuses on the use of the Attained Age Normal (AAN) method in calculating pension funds for pension program participants at PT Taspen Cirebon Branch Office. In addition, this study also compares the results of the AAN method calculation with another method, namely Projected Unit Credit (PUC), to see the advantages and disadvantages of each method. The AAN method calculates liabilities based on the current age of the participant, thus providing more conservative results and tending to be stable in the long term. The results showed that the AAN method produced a higher total normal contribution compared to the PUC method. Normal contributions calculated by the AAN method for participants of the PT Taspen pension program at the Cirebon Branch Office showed an increase of 2,095,355.33 rupiah at the age of 32 years. On the other hand, the PUC method produces a lower normal contribution, which is 827,843.62 rupiah for the same age. In terms of actuarial obligations, the AAN method also shows a more significant increase than PUC. These results show that the AAN method is more stable in the calculation of actuarial liabilities, although it requires larger contributions. Thus, although the Attained Age Normal (AAN) method results in higher normal contributions, it provides better assurance in maintaining the company's financial balance in the long term. This study provides a recommendation that PT Taspen can consider the AAN method as a more conservative alternative in pension fund management.
Analysis The Effect Of Volatility On Potential Losses Mutual Fund Investments Using The ES-GARCH Method Pamungkas, Abram Chandra Aji; Subartini, Betty; Susanti, Dwi
International Journal of Quantitative Research and Modeling Vol 5, No 3 (2024)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v%vi%i.594

Abstract

Investing in mutual funds has become a popular choice for investor who looking to participate in the capital markets with more diversified risk. However, the success of mutual fund investments depends on investors understanding the potential losses and opportunities that may arise during the investment period. Analyzing the risk of mutual fund investments is fundamental in helping investors comprehend potential losses. Therefore, research is conducted to understand potential losses by estimating asset price volatility and determining the maximum possible losses. The Expected Shortfall (ES) method proves useful in measuring downside risk and extreme loss potential in investments, but it is less effective in addressing nonlinear trends and the complexity of volatility patterns. Hence, a combination of the Expected Shortfall (ES) and Generalized Autoregressive Conditional Heteroskedasticity (GARCH) methods is employed to measure the risk of mutual fund investments. The research findings indicate that volatility has a positive impact on Value at Risk (VaR), and the potential maximum losses (ES) increase with higher volatility, indicating a greater risk.
Analysis of Microinsurance Demands Combined with Microcredit on Rice Farming by Using Utility Function Apipah Jahira, Juwita; Subartini, Betty; Sukono, Sukono
Operations Research: International Conference Series Vol. 2 No. 3 (2021): Operations Research International Conference Series (ORICS), September 2021
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v2i3.175

Abstract

Agriculture is a business that is prone to risk and uncertainty so farmers can face serious difficulties at any time. Especially for farmers in developing countries who are generally small farmers. To anticipate these risks and uncertainties, farmers can take agricultural insurance or apply for credit. Even though an agricultural insurance program is available, farmers are constrained by the limited amount of collateral and liquidity constraints. This study aims to analyze the demand for microinsurance combined with microcredit in rice farming. The analysis is carried out with utility functions and utility comparisons using ordinal comparison. Meanwhile, to determine optimal demand by maximizing the utility using an ordinal approach through analysis of budget line and indifference curve. The results show that the demand for insurance and the profitability of agricultural credit increases along with the lower demand for collateral when applying for agricultural loans. In addition, microinsurance combined with microcredit is more profitable for farmers when collateral is not requested when applying for agricultural credit. Based on the results of the case study, the optimal demand is obtained when the premium for Rice Farming Business Insurance (AUTP) is and the installments of BNI People’s Business Credit (BNI KUR) is
Profit and Loss Report of DSH Meat Stalls in Panumbangan Market Zahra, Ami Emilia Putri; Subartini, Betty
Operations Research: International Conference Series Vol. 3 No. 3 (2022): Operations Research International Conference Series (ORICS), September 2022
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v3i3.186

Abstract

DSH Meat Kiosk is a kiosk that sells one of the foodstuffs, namely Beef. This DSH Meat Stall has been established for more than 20 years. However, as long as the kiosk has been standing, the manager still finds it challenging to analyze profits from sales. Therefore, the Preparation of a Profit - Loss Financial Report is intended to assist traders in managing the profits generated. This report makes a financial analysis of November 2021 and February 2022. The method used in preparing this report is using primary data by collecting data in the form of interviews with kiosk owners regarding matters needed in preparing profit and loss reports such as assets held and owned, total income, operational costs and others. The results of this report show that sales in February 2022 decreased by 17.88% compared to November 2021. It is hoped that this report will help and make it easier to manage the profit generated and make decisions to make the best profit.
Food Sector Stock Investment Portfolio Optimization using Mean-Expected Shortfall Model with Particle Swarm Optimization Tampubolon, Carlos Naek Tua; Subartini, Betty; Sukono, Sukono
Operations Research: International Conference Series Vol. 4 No. 3 (2023): Operations Research International Conference Series (ORICS), September 2023
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v4i3.252

Abstract

One of the most promising investment products is stocks. Stocks have great profit potential, but the risks associated with this investment should not be ignored by investors. Therefore, an optimal investment strategy is needed by forming an investment portfolio, in order to minimize risk and maximize profits that can be obtained. This study aims to optimize the investment portfolio. The method used in this research is based on the Mean-Expected Shortfall (Mean-ES) model. The use of this method is expected that investors can get a more accurate picture of the level of risk associated with their stock portfolio. In addition, Particle Swarm Optimization (PSO) can also be used to optimize the allocation of funds in a stock portfolio.  Applying PSO, investors can find the optimal combination of fund allocation to achieve a high level of return. Based on the results of the analysis conducted on the following five stocks AALI, BISI, DSNG, LSIP and SMAR, the results show a risk level of 0.0014 and a return level of 0.021%.  Thus, investors can form a stock portfolio that has a high potential return, while minimizing the risks associated with stock investment. The implementation of this optimal investment strategy can assist investors in achieving their financial goals in a more effective manner.  Considering the potential returns and risks involved, investors can make wiser investment decisions and optimize the performance of their stock portfolio.
The Use of Quasi Monte Carlo Method with Halton Random Number Sequence in Determining the Price of European Type Options: in PT Telekomunikasi Indonesia Stock’s Putri, Sherina Anugerah; Subartini, Betty; Sukono, Sukono
International Journal of Global Operations Research Vol. 3 No. 4 (2022): International Journal of Global Operations Research (IJGOR), November 2022
Publisher : iora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/ijgor.v3i4.191

Abstract

An investor must be wise in managing the funds he has to carry out investment activities. Investors can use options as an alternative to investing because they can increase profits and avoid investment risks. Options are one of the most widely used derivative products. The main problem when entering into an option contract is determining the right price to be paid by the option buyer to the option seller. This research was made to determine the price of European-type stock options. Case studies on PT Telekomunikasi Indonesia, Tbk shares in the 2021-2022 period. The analysis was performed using the Quasi-Monte Carlo method with Halton's random number sequence. Based on the results of this study, it is expected to be a consideration in deciding to buy European-type stock options at PT Telekomunikasi Indonesia, Tbk
Actuarial Pension Fund Using the Projected Unit Credit (PUC) Method: Case Study at PT Taspen Cirebon Branch Office Amalia, Hana Safrina; Subartini, Betty; Sukono, Sukono
International Journal of Quantitative Research and Modeling Vol 5, No 3 (2024)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v5i3.745

Abstract

The pension fund program is a program held by the government to ensure the welfare of Civil Servants (PNS) in retirement as old-age security. The pension program for civil servants is managed by a pension fund, PT Taspen (Persero). Actuarial calculations of pension funds need to be carried out to determine the amount of normal contributions and actuarial liabilities that must be paid by pension plan participants and companies. The actuarial calculation of pension funds used by PT Taspen in managing civil servant pension funds is the Accrued Benefit Cost which determines in advance the benefits that will be obtained by participants. The Projected Unit Credit (PUC) method is one part of the Accrued Benefit Cost. This study aims to determine normal contributions and actuarial liabilities using the Projected Unit Credit (PUC) method for civil servant pension program participants of PT Taspen (Persero) Cirebon Branch Office. The calculation results show that the PUC method provides a more accurate calculation of the estimated normal contributions and actuarial liabilities of the company. This study is expected to be a reference for other companies in managing employee pension funds using an actuarial approach.
Comparison of Stock Price Forecasting with ARIMA and Backpropagation Neural Network (Case Study: Telkom Indonesia) Carissa, Katherine Liora; Subartini, Betty; Sukono, Sukono
International Journal of Quantitative Research and Modeling Vol 6, No 1 (2025)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v6i1.896

Abstract

The growth of capital market investors in Indonesia is increasing every year. The most popular investment instrument is stocks. One of the stocks on the Indonesia Stock Exchange (IDX) is the Telkom Indonesia (TLKM). Through stock investment, investors can make a profit by utilizing stock prices in the market. However, stock price fluctuations are uncertain. Therefore, modeling is needed to be able to predict stock prices more accurately. The purpose of this study was to find an appropriate time series model and Neural Network model architecture, and to measure the accuracy of the two models in predicting future stock prices of TLKM. The study was conducted using the Autoregressive Integrated Moving Average (ARIMA) model and Backpropagation Neural Network (BPNN). For comparison, the Mean Absolute Percentage Error (MAPE) method was used. The data used in both models were the stock prices of Telkom Indonesia (TLKM) from September 1, 2023 to September 30, 2024. The result shows that the best ARIMA model, selected based on the least Akaike Information Criterion (AIC) value, is ARIMA(0,1,3) with a MAPE value of 1.20%. Meanwhile, the best BPNN model selected from the smallest testing Mean Squared Error (MSE) value, is BPNN(1,3,1) with a MAPE value of 1.17%. Among those two models, the BPNN model is more accurate because it has less MAPE value compared to the ARIMA one. The results of this research can be considered in forecasting TLKM stock price in the future.
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.
IDX30 Stock Portfolio Optimization Using Genetic Algorithm Based on Capital Asset Pricing Model Rahmadhisa, Nayra Pavita; Susanti, Dwi; Subartini, Betty
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.v6i2.981

Abstract

The stock market plays a vital role in supporting economic growth by serving as a primary channel for companies to raise capital and for investors to gain profits through long-term investments. In practice, one of the biggest challenges for investors is identifying which stocks are worth purchasing and how to allocate their funds optimally. One commonly used approach to evaluate stock feasibility is the Capital Asset Pricing Model (CAPM), which helps identify undervalued and overvalued stocks based on the relationship between systematic risk and expected return. Additionally, it is necessary to determine the optimal investment weight allocation. Therefore, this study combines the CAPM method for stock selection and Genetic Algorithm, a metaheuristic approach capable of finding optimal solutions in complex problems, to determine the optimal portfolio weight composition. The object of this study includes stocks listed in the IDX30 index during the period from February 2021 to November 2023. The results show that five stocks—ADRO, BBCA, BBNI, KLBF, and TLKM—are classified as undervalued according to the CAPM method and are recommended for inclusion in the optimal portfolio. Portfolio optimization using the Genetic Algorithm results in the following stock weight composition: ADRO 26.55%, BBCA 36.20%, BBNI 9.09%, KLBF 12.20%, and TLKM 15.96%, with a Sharpe Ratio of 4.043906. The expected return and risk of the optimal portfolio are 0.00067373 and 0.00012407, respectively.
Co-Authors - Riaman Adib, Andhita Zahira Agus Santoso Agus Supriatna Agus Supriatna Aisyah Nurul Aini Alfan Azkiya Robbani Amalia, Hana Safrina Annisa Aprillia Annisa Nur Falah Annisa Nur Falah, Annisa Nur Apipah Jahira, Juwita Ary Robayani Asep K Supriatna Asep K Supriatna, Asep K Asri Rula Hanifah Azimah Lisan Robbani Banowati, Puspa Dwi Ayu Budi N. Ruchajana Budi N. Ruchajana, Budi N. Carissa, Katherine Liora Diah Chaerani Dian Nuryani Dini Aulia Dwi Susanti Eddy Djauhari Edi Kurniadi Edi Kurniadi Edi Kurniadi Edi Kurniadi Edi Kurniadi Elis Hertini Endang Rusyaman Endang Soeryana Hasbullah Felfin Ulfah Annisa Firdaniza Firdaniza Firdaus, Muhammad Rayhan Ghazali, Puspa Liza Herlina Napitupulu Jeane R. M. D. P Chantique Jumadil Saputra Kankan Parmikanti Muhammad Iqbal Al-Banna Ismail Nahda Nabiilah Novitasari, Ela Nurdyah, Himda Anataya Nursanti Anggriani Nurul Fadilah Nurul Gusriani, Nurul Olivia Anjanette Pamungkas, Abram Chandra Aji Putri Adhira Novalia Putri Chaerunnisa Febryanti Putri, Sherina Anugerah R Wulantini R Wulantini, R Rahmadhisa, Nayra Pavita Rahman, Rezki Aulia Reisnanda, Aldino Riaman . Riaman Riaman Riaman Riaman Riaman Riaman Riaman Riaman, Riaman Risdawati Risdawati Sampath, Sivaperumal Saputra, Jumadil Sianturi, Sri Novi Elizabeth Silvia Wijaya Sisilia Sylviani Sonia . Sukono Sukono Tampubolon, Carlos Naek Tua Tegar Ridwansyah Yeremia Herry Parulian Yeremia Herry Parulian, Yeremia Herry Zahra, Ami Emilia Putri Zakirah, Khalilah Razanah