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Hidayana, Rizki Apriva

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Religion Humanities Computer Science & IT Decision Sciences, Operations Research & Management Dentistry Economics, Econometrics & Finance Education Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Mathematics Medicine & Pharmacology Nursing Physics Public Health Social Sciences Transportation Other

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Value-at-Risk Estimation of Indofood (ICBP) and Gas Company (PGAS) Stocks Using the ARMA-GJR-GARCH Model Napitupulu, Herlina; Hidayana, Rizki Apriva; Saputra, Jumadil
Operations Research: International Conference Series Vol. 2 No. 4 (2021): Operations Research International Conference Series (ORICS), December 2021
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v2i4.183

Stocks are one of the most widely used financial market instruments by investors in investing. The most important component of any investment is volatility. Volatility is a conditional measure of variance in stock returns and is important for risk management. In addition to volatility, the important things in investing are return and risk. Risk can be measured using Value-at-Risk (VaR) and can estimate the maximum loss that occurs. The purpose of this study is to determine VaR using the Autoregressive Moving Average-Glosten Jagannatan Runkle-Generalized Autoregressive Conditional Heteroscedasticity (ARMA-GJR-GARCH) model. The stages of data analysis used are estimating the ARMA model and the GARCH model, then estimating the GJR-GARCH model by looking at the heteroscedasticity and asymmetric effects on the GARCH model. Next, determine the VaR value from the estimated mean and variance (volatility) using the ARMA-GJR-GARCH model. The results of the model estimator obtained are based on the return data for the four stocks analyzed, namely the ARMA (5,5)-GJR-GARCH (1,1) model for ICBP stocks and ARMA (1,2)-GJR-GARCH (1,1) for PGAS shares. The Value-at-Risk values of each stock are 0.060427 and 0.024724. This research can be used by investors as a consideration in making investment decisions.

Pension Fund Calculation Using Traditional and Projected Unit Credit Methods for Total Actuarial Liability and Normal Cost Cases Daulay, Syifa Nur Rasikhah; Hidayana, Rizki Apriva; Halim, Nurfadhlina Abdul
Operations Research: International Conference Series Vol. 3 No. 4 (2022): Operations Research International Conference Series (ORICS), December 2022
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v3i4.195

The DSH Meat Kiosk is a kiosk that sells one of the foodstuffs, namely Beef. This DSH Meat Kiosk has been around for more than 20 years. However, as long as this kiosk is established, the manager still finds it difficult to analyze the profit from the sale. Therefore, this Profit and Loss Financial Statement is intended to assist traders in managing the profits generated. In this report a financial analysis is made in November 2021 and February 2022. The method used in making this report is to use primary data by collecting data in the form of interviews with kiosk owners relating to things needed in making profit and loss statements such as assets that owned, total revenue, operating costs and others. The results of this report show that sales in February 2022 decreased by 17.88% compared to November 2021. With this report, it is hoped that this report will help and make it easier to manage the profits generated and make decisions to generate the best profits.The discussion of the selected questions will look for what actuarial obligations are and what normal costs are based on the data provided. The purpose of this discussion is to know, understand, and be able to perform actuarial calculations regarding the unit credit method used. The unit credit method used is the traditional unit credit and the projected unit credit. The formula used for each question is as follows.Â andThe result of solving the first problem shows that the total actuarial liability on 1/1/95 is IDR 405,339.095. While the results of the second question show that the normal cost for 2021 on 1/1/2021 was IDR 1,071.43. From these results, users can find out how much actuarial obligations are and what normal costs are based on the data that has been provided.

Investment Portfolio Optimization using Mean-Semi Standard Deviation Model (Case Study: BBNI, BBCA, BMRI, TLKM, and ANTM) Saputra, Moch Panji Agung; Hidayana, Rizki Apriva; Laksito, Grida Saktian
Operations Research: International Conference Series Vol. 5 No. 4 (2024): Operations Research International Conference Series (ORICS), December 2024
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v5i4.353

This study aims to determine the optimal stock portfolio allocation using the Mean-Semi Standard Deviation optimization model as an alternative to the more commonly used Mean-Variance model. The Mean-Semi Standard Deviation model considers downside risk, which is more relevant to investors' preferences in minimizing potential losses. The data used in this study consists of daily closing prices of five stocks listed on the Indonesia Stock Exchange (BBNI, BBCA, BMRI, TLKM, and ANTM) from December 7, 2023, to December 6, 2024. The optimization process was conducted using the Lagrange method to maximize the portfolio's expected return with controlled risk, incorporating a risk aversion parameter (ro) to adjust for investor preferences. The results show that the portfolio with a risk aversion value of ro=0.1 provides the highest return-to-risk ratio of 0.058556, with the largest portfolio weight allocated to BBCA stock. The findings suggest that the Mean-Semi Standard Deviation model can serve as a more effective approach to portfolio management in the Indonesian stock market, particularly in reducing downside risk amid high market volatility.

Analysis of Queueing Systems in Fast Food Restaurants Using the M/M/c Model: A Case Study during Peak Hours Hidayana, Rizki Apriva; Yohandoko, Setyo Luthfi Okta
International Journal of Global Operations Research Vol. 5 No. 4 (2024): International Journal of Global Operations Research (IJGOR), November 2024
Publisher : iora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/ijgor.v5i4.341

This study evaluates the queueing system of a fast-food restaurant using the M/M/c model to optimize the number of service counters (servers) for reducing customer waiting times during peak hours. The analysis involved simulating different configurations with 1, 2, and 3 servers, considering a customer arrival rate of 20 customers per minute and a service rate of 25 customers per minute. Results demonstrate a clear relationship between the number of servers and system performance. A single-server system resulted in an average total time of 12 seconds per customer in the system, highlighting significant delays during peak times. Introducing a second server reduced the average waiting time in the system to 4.44 seconds, striking an effective balance between service efficiency and resource utilization. However, adding a third server showed minimal improvement, as the system's utility ratio declined significantly, suggesting underutilized resources. Based on these findings, a two-server configuration is identified as the optimal solution, efficiently managing the customer arrival rate while maintaining a balanced utility ratio. This study emphasizes the practical value of combining queueing models and simulations to improve operational efficiency in fast-food service systems. The insights can guide decision-making processes for restaurant managers aiming to enhance customer satisfaction and optimize resource allocation during high-demand periods.

Modeling of COVID-19 Growth Cases in Bandung Regency and Bandung City Using Vector Autoregression Megantara, Tubagus Robbi; Hidayana, Rizki Apriva; Syarifudin, Abdul Gazir; Amelia, Rika; Nurkholipah, Nenden Siti
International Journal of Global Operations Research Vol. 5 No. 4 (2024): International Journal of Global Operations Research (IJGOR), November 2024
Publisher : iora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/ijgor.v5i4.342

COVID-19 is a global health epidemic due to increasing infections and deaths. Indonesia has many confirmed cases with high daily case growth, including the Bandung City and Bandung Regency areas. High mobility between regions can impact the growth of COVID-19 cases. Strategies to prevent the growth of COVID-19 cases need to be carried out by considering the growth of COVID-19 cases in the nearest area. The Vector Autoregression (VAR) model is a forecasting model that can consider geographic impacts. This study aims to model the growth of cases in adjacent areas and have high mobility using the VAR method. The growth of COVID-19 cases in Bandung City and Bandung Regency is integrated into the VAR model to see the impact of each other. The VAR model also considers the impact of case growth in the past on its region's future. Transformation and differencing are carried out on the time series of case growth in each region to achieve time-series stationarity so that the VAR model can be carried out. First-order VAR becomes a model representing the growth of COVID-19 cases in Bandung City and Bandung Regency. The model shows that COVID-19 cases in each region will decrease over time and each region impacts each other. Decreasing cases growth can be caused because people who have been infected and vaccinated have sound immune systems to prevent re-infection. However, prevention still needs to be done to stop the pandemic. Therefore, restrictions on mobility between regions can be used as a strategy to prevent COVID-19 infection.

Determination of Collective Premiums for Seven Benefits of BPJS Employment Insurance JKK Program Using Poisson-Normal Aggregate Distribution Maghfirani, Nazla Aqira; Hidayana, Rizki Apriva
International Journal of Business, Economics, and Social Development Vol 6, No 1 (2025)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijbesd.v6i1.877

Work Accident Insurance (JKK) is one of the programs of the Social Security Administering Agency (BPJS) for Employment. Insurance brokers need to make an initial estimate of the premium to determine the collective premium for JKK. Premium calculations can be done using the aggregate distribution method. The total loss of the insurance policy can be owned by the random variable of the aggregate distribution. In calculating the premium using the aggregate distribution, one of the principles that can be used is the standard deviation principle. Based on this principle, the amount of the premium can be calculated by the standard deviation of the aggregate distribution. This study uses the aggregate Poisson-Normal distribution to calculate the collective premium based on the seven benefits of the JKK BPJS Ketenagakerjaan Bojongsoang program. The data used are the number of claim events and the number of claims from the seven benefit claims of JKK BPJS Ketenagakerjaan Bojongsoang participants for the 2022 period. The principle used in calculating the collective premium with the aggregate distribution is the standard deviation principle. The results of the analysis show that the Poisson distribution is followed by claim frequency data and the Normal distribution is followed by the amount of the claim. This study shows that the amount of collective premium calculated tends to be greater than the amount of collective premium sourced from existing data of BPJS Ketenagakerjaan Bojongsoang company. It is expected for insurance brokers and insurance companies to consider this study.

Analysis of Economic Growth and Tourism Potential in Tanjung Lesung, Panimbang, Banten as a Creative Economy Destination Hidayana, Rizki Apriva; Lestari, Mugi
International Journal of Business, Economics, and Social Development Vol 6, No 1 (2025)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijbesd.v6i1.879

Tanjung Lesung, located in Pandeglang Regency, Banten, has been designated as a Special Economic Zone (SEZ) for Tourism with the aim of encouraging regional economic growth and improving community welfare. This study analyzes the impact of SEZ on the local economy using qualitative and quantitative approaches. Data were obtained through in-depth interviews, surveys, field observations, and documentation studies. The results of the study indicate that the Tanjung Lesung SEZ has contributed positively to increasing community income by 52% and reducing the unemployment rate by 33%. In addition, investment in the tourism sector encourages business growth in the hospitality, culinary, and tourism services sectors. However, the development of SEZ also faces several challenges, such as limited infrastructure, readiness of local workers, and social and environmental impacts. Limited infrastructure, especially transportation access, is an obstacle in supporting the growth of the tourism sector. In addition, many local workers do not yet have the skills needed by the tourism industry. Environmental impacts, such as increasing waste volume and conversion of agricultural land, are also major concerns. Therefore, a comprehensive strategy is needed through improving infrastructure, strengthening human resource capacity, and implementing sustainable environmental management policies. With the right steps, Tanjung Lesung Special Economic Zone can become a successful model for inclusive and sustainable tourism-based economic development in Indonesia.

Analysis Testing Black Box and White Box on Application To-Do List Based Web Pirdaus, Dede Irman; Hidayana, Rizki Apriva
International Journal of Mathematics, Statistics, and Computing Vol. 2 No. 2 (2024): International Journal of Mathematics, Statistics, and Computing
Publisher : Communication In Research And Publications

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijmsc.v2i2.95

The rapid development of information technology has led to the creation of numerous web-based applications designed to assist human activities and work. One such application is the To-Do List, which helps users manage their tasks and increase productivity. This study aims to analyze the quality of web-based To-Do List applications through black box and white box testing. The research focuses on the login and main pages of the application, where various scenarios are tested to ensure that the system functions as intended. The testing process includes designing test scenarios, creating test cases, executing the test cases, and collecting and processing test result data. The study also includes an analysis of the program's source code using flowcharts and flowgraphs to identify the number of independent logic execution paths and design test cases for white box testing. The results of the testing will help identify errors and weaknesses in the application, ensuring that the final product is of high quality.

Optimization of Stock Portfolio in Indonesian Health Sector using Markowitz Modern Portfolio Theory Kalfin; Hidayana, Rizki Apriva
International Journal of Mathematics, Statistics, and Computing Vol. 3 No. 1 (2025): International Journal of Mathematics, Statistics, and Computing
Publisher : Communication In Research And Publications

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijmsc.v3i1.182

This study analyzes the optimization of the health sector stock portfolio on the Indonesia Stock Exchange using the Markowitz Modern Portfolio Theory method. The data used are the daily closing prices of health sector stocks over the last three years obtained through web scraping techniques from Yahoo Finance. The analysis includes the calculation of daily returns, daily risks, and covariance matrices between stocks. The results of the portfolio optimization show that out of the ten stocks analyzed, the optimal portfolio consists of four stocks, namely MIKA.JK (62.82%), KLBF.JK (15.58%), CARE.JK (15.37%), and SAME.JK (6.23%). This portfolio generates a daily return of 0.216% with a risk level of 1.996%. MIKA.JK contributes the highest return of 0.02063% with a risk of 1.52601%. This study provides guidance for investors in optimizing fund allocation in the health sector stock portfolio in Indonesia.

Matching Riders to Drivers Under Uncertain Wait Times in Ride-Hailing Systems: A Robust Optimization Approach with Box Uncertainty Megantara, Tubagus Robbi; Hidayana, Rizki Apriva
International Journal of Mathematics, Statistics, and Computing Vol. 3 No. 2 (2025): International Journal of Mathematics, Statistics, and Computing
Publisher : Communication In Research And Publications

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijmsc.v3i2.202

The advent of ride-hailing systems has revolutionized urban mobility, yet efficient vehicle assignment remains challenging due to inherent uncertainties in passenger waiting times. This study addresses the ride-hailing matching problem under uncertain wait times, proposing a robust optimization model with a box uncertainty set to mitigate the impact of variability in service delivery. We first contextualize the problem by examining the evolution of transportation systems, emphasizing how ride-hailing services complicate traditional matching paradigms. Existing approaches often fail to account for real-world unpredictability, leading to suboptimal assignments. To bridge this gap, we formulate a data-driven robust optimization framework that bounds waiting time fluctuations within a box uncertainty set, ensuring reliable performance under worst-case scenarios. Using simulation data from Manhattan taxi trips, we compare our robust model against deterministic benchmarks, demonstrating its superiority in reducing average waiting times and enhancing system reliability, even under high uncertainty. Our results highlight the practical viability of robust optimization for ride-hailing platforms operating in dynamic environments.

Co-Authors Abdul Gazir Syarifudin Agustin, Nemia Amal, Moh Alfi Amelia, Rika Azahra, Astrid Sulistya Chairunnisa, Nadine Zahra Daulay, Syifa Nur Rasikhah Dewi Ratnasari Halim, Nurfadhlina Abdul Haq, Fadiah Hasna Nadiatul Harahap, Reivani Putri Berlinda Hasanah, Indah Mauludina Herlina Napitupulu Ibrahim, Riza Andrian kalfin Kalfin Kalfin, Kalfin Khan, Muhammad Fardeen Kholipah, Nenden Siti Nur Kisti, Vuji Annisa Laksito, Grida Saktian Lianingsih, Nestia Maghfirani, Nazla Aqira Manuela, Angellyca Leoni Megantara, Tubagus Robbi Meizani, Nicko Mugi Lestari, Mugi Mulyo, Lukman Widoyo Nenden Siti Nurkholipah, Nenden Siti Pirdaus, Dede Irman Riaman Riaman, Riaman Rini Cahyandari Saefullah, Rifki Saputra, Jumadil Sidiq, Fahmi Sukono Sukono Tiswaya, Waway Yakubu, Usman A. Yoefitri, Tina Yohandoko, Setyo Luthfi Okta Yuningsih, Siti Hadiaty

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