Garuda - Garba Rujukan Digital

p-Index From 2021 - 2026

5.963

P-Index

This Author published in this journals

Hidayana, Rizki Apriva

Unknown Affiliation

Author-ID : 7476020

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

Published : 47 Documents Claim Missing Document

Claim Missing Document

Articles

Title

Training on Basic Mathematics for 12th Grade Students of SMA Pasundan Majalaya in Preparation for the 2024 SNBT Hidayana, Rizki Apriva; Yuningsih, Siti Hadiaty; Syarifudin, Abdul Gazir; Amelia, Rika; Nurkholipah, Nenden Siti
Operations Research: International Conference Series Vol. 5 No. 2 (2024): Operations Research International Conference Series (ORICS), June 2024
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v5i2.316

Basic math training plays an important role in preparing students for the National Selection Based Test (SNBT), which is one of the entry pathways to public universities in Indonesia. This study aims to evaluate the effectiveness of academic ability test training in improving the readiness of XII grade students of Pasundan Majalaya High School to face SNBT 2024. The research method used is descriptive quantitative with a case study approach. The study population was all XII grade students of Pasundan Majalaya High School who participated in the training program. Data were collected through observations and tests conducted before and after the training. Data analysis was conducted to measure the improvement of students' academic ability and readiness. The results showed that the academic proficiency test training implemented at Pasundan Majalaya High School was effective in improving students' pre and post test results. There was a significant increase in proficiency test scores through pre and post test results. In addition, the training also helped students in developing time management skills, problem solving strategies, and critical thinking skills. The findings suggest that structured and comprehensive training can significantly improve students' academic readiness, thus helping them to face SNBT more confidently and competitively. This research is expected to contribute to the preparation of Pasundan Majalaya High School students for college entrance selection.

Estimated Value-at-Risk Using the ARIMA-GJR-GARCH Model on BBNI Stock Hidayana, Rizki Apriva; Napitupulu, Herlina; Sukono, Sukono
Operations Research: International Conference Series Vol. 5 No. 2 (2024): Operations Research International Conference Series (ORICS), June 2024
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v5i2.317

Stocks are investment instruments that are much in demand by investors as a basis in financial storage. Return and risk are the most important things in investing. Return is a complete summary of investment and the return series is easier to handle than the price series. The movement of risk of loss is obtained from stock investments with profits. One way to calculate risk is value-at-risk. The movement of stocks is used to form a time series so that the calculation of risk can use time series. The purpose of this study was to find out the Value-at-Risk value of BBNI Shares using the ARIMA-GJR-GARCH model. The data used in this study was the daily closing price for 3 years. The time series method used is the model that will be used, namely the Autoregressive Integrated Moving Average (ARIMA)-Glosten Jagannathan Runkle - generalized autoregressive conditional heteroscedastic (GJR-GARCH) model. The stage of analysis is to determine the prediction of stock price movements using the ARIMA Model used for the mean model and the GJR-GARCH model is used for volatility models. The average value and variants obtained from the model are used to calculate value-at-risk in BBNI shares. The results obtained are the ARIMA(1,0,1)-GJR-GARCH(1.1) model and a significance level of 5% obtained value-at-risk of 0.0705.

Implementing the Variance-Covariance Method for Assessing Market Transaction Risks in Raw Material Sector Stocks Kisti, Vuji Annisa; Haq, Fadiah Hasna Nadiatul; Hidayana, Rizki Apriva
Operations Research: International Conference Series Vol. 5 No. 2 (2024): Operations Research International Conference Series (ORICS), June 2024
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v5i2.310

The capital market plays a crucial role in supporting a country's economic growth. Besides being a funding source, the capital market also serves as an investment avenue for investors, particularly through stocks. Every investor must be willing to bear risks in line with their targeted returns. Risk is defined as the uncertainty of future outcomes due to market condition changes, and VaR (Value at Risk) is used to determine the tolerated loss at a certain confidence level. This study discusses the application of the Value at Risk (VaR) method using the Variance-Covariance approach to mitigate market risks in the portfolio of raw material sector stocks. The study focuses on two raw material sector stocks in Indonesia, assuming a normal distribution of asset price changes. The measurement results indicate that with an investment of Rp. 100,000,000.00, a 95% confidence level, and a 1-day period, the VaR of the portfolio of these five stocks is Rp. 2,769,750.00. This research provides critical insights to assist investors in understanding and managing portfolio risks, making VaR a key indicator to measure potential future risks and laying the foundation for decision-making in risk management.

Determination of Risk Value Using the ARMA-GJR-GARCH Model on BCA Stocks and BNI Stocks Hidayana, Rizki Apriva; Napitupulu, Herlina; Saputra, Jumadil
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.v2i3.176

Stocks are common investments that are in great demand by investors. Stocks are also an investment instrument that provides returns but tends to be riskier. The return time series is easier to handle than the price time series. In investment activities, there are the most important components, namely volatility and risk. All financial evaluations require accurate volatility predictions. Volatility is identical to the conditional standard deviation of stock price returns. The most frequently used risk calculation is Value-at-Risk (VaR). Mathematical models can be used to predict future stock prices, the model that will be used is the Glosten Jagannathan Runkle-generalized autoregressive conditional heteroscedastic (GJR-GARCH) model. The purpose of this study was to determine the value of the risk obtained by using the time series model. GJR-GARCH is a development of GARCH by including the leverage effect. The effect of leverage is related to the concept of asymmetry. Asymmetry generally arises because of the difference between price changes and value volatility. The method used in this study is a literature and experimental study through secondary data simulations in the form of daily data from BCA shares and BNI shares. Data processing by looking at the heteroscedasticity of the data, then continued by using the GARCH model and seeing whether there is an asymmetry in the data. If there is an asymmetric effect on the processed data, then it is continued by using the GJR-GARCH model. The results obtained on the two stocks can be explained that the analyzed stock has a stock return volatility value for the leverage effect because the GJR-GARCH coefficient value is > 0. So, the risk value obtained by using VaR measurements on BCA stocks is 0.047247 and on BNI stocks. is 0.037355. Therefore, the ARMA-GJR-GARCH model is good for determining the value of stock risk using VaR.

Determination of VaR on BBRI Stocks and BMRI Stocks Using the ARIMA-GARCH Model Napitupulu, Herlina; Hidayana, Rizki Apriva; Saputra, Jumadil
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.v2i3.178

Stocks are investment instruments that are much in demand by investors as a basis in financial storage. Return and risk are the most important things in investing. Return is a complete summary of investment and the return series is easier to handle than the price series. The movement of risk of loss is obtained from stock investments with profits. One way to calculate risk is value-at-risk. The movement of stocks is used to form a time series so that the calculation of risk can use time series. The purpose of this study was to find out the Value-at-Risk value of BBRI and BMRI stock using the ARIMA-GARCH model. The data used in this study was the daily closing price for 3 years. The time series method used is the Autoregressive Integrated Moving Average (ARIMA)-Generalized Autoregressive Conditional Heteroscedastic (GARCH) model. The stage of analysis is to determine the prediction of stock price movements using the ARIMA model used for the mean model and the GARCH model is used for volatility models. The average value and variants obtained from the model are used to calculate value-at-risk in BBRI and BMRI stock. The results obtained are the ARIMA(3,0,3)-GARCH(1,1) and ARIMA(2,0,2)-GARCH(1,1) model so with a significance level of 5% obtained Value-at-Risk of 0.04058 to BBRI stock and 0.10167 to BMRI stock.

Determination of Value-at-Risk in UNVR Stocks Using ARIMA-GJR-GA RCH Model Hidayana, Rizki Apriva; Napitupulu, Herlina; Sukono, Sukono
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.v2i4.181

Stocks are investment instruments that are in great demand by investors as a basis for storing finances. The most important thing in investing is the return and risk of loss obtained from investing in stocks. Risk measurement is carried out using Value-at-Risk and Conditional Value-at-Risk. The stock movements used are historical data and in the form of time series, so that a model can be formed to predict the next movement of stocks and risk measurements can be carried out. The purpose of this study is to determine the value of risk obtained by investors using time series analysis. The data used in this study is the daily closing price of stocks for 3 years. The stages of the analysis carried out to predict stock movements are to determine the ARIMA model for the mean model and the GJR-GARCH model for the volatility model. The mean value and variance are used to calculate the risk value of VaR. Based on the results of the Value-at-Risk calculation obtained, UNVR shares have a risk value of 0.01217. This means that if an investment is made in UNVR shares of IDR 100,000,000.00, the estimated maximum loss of potential loss that occurs is estimated to reach IDR 1,217,000.

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.

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

Title Search

Found 9 Documents Search Journal : Operations Research: International Conference Series

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Abstract

Title

Found 9 Documents
Search
Journal : Operations Research: International Conference Series