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All Journal EKSAKTA: Journal of Sciences and Data Analysis Media Statistika MATEMATIKA Bionatura Statistika CAUCHY: Jurnal Matematika Murni dan Aplikasi SEMIRATA 2015 Kubik JURNAL ILMU MANAJEMEN DAN BISNIS Jurnal Matematika Sains dan Teknologi Jurnal Teknik Industri: Jurnal Keilmuan dan Aplikasi Teknik Industri BAREKENG: Jurnal Ilmu Matematika dan Terapan Zero : Jurnal Sains, Matematika, dan Terapan Teorema: Teori dan Riset Matematika International Journal of Supply Chain Management Jambura Journal of Mathematics Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika Jurnal Ilmiah Matematika dan Pendidikan Matematika (JMP) InPrime: Indonesian Journal Of Pure And Applied Mathematics SMART SPORT KUBIK: Jurnal Publikasi Ilmiah Matematika International Journal of Business, Economics, and Social Development International Journal of Research in Community Services Operations Research: International Conference Series International Journal of Global Operations Research International Journal of Quantitative Research and Modeling International Journal of Ethno-Sciences and Education Research Jurnal Matematika Integratif Agridev Journal : Agribusiness Digitalization & Community Development Mathematical Sciences and Applications Journal International Journal of Technology and Education Research Indonesian Actuarial Journal
Sukono Sukono
Jurusan Matematika, Fakultas Matematika Dan Ilmu Pengetahuan Alam, Universitas Padjadjaran, Bandung, Indonesia
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Journal : Operations Research: International Conference Series

 1   2 
Application of ARIMA-GARCH Model for Prediction of Indonesian Crude Oil Prices Sukono, Sukono; Suryamah, Emah; Novinta S, Fujika
Operations Research: International Conference Series Vol. 1 No. 1 (2020): Operations Research International Conference Series (ORICS), March 2020
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v1i1.21

Abstract

Crude oil is one of the most important energy commodities for various sectors. Changes in crude oil prices will have an impact on oil-related sectors, and even on the stock price index. Therefore, the prediction of crude oil prices needs to be done to avoid the future prices of these non-renewable natural resources to increase dramatically. In this paper, the prediction of crude oil prices is carried out using the Auto-Regressive Integrated Moving Average (ARIMA) and Generalized Auto-Regressive Conditional Heteroscedasticity (GARCH) models. The data used for forecasting are Indonesian Crude Price (ICP) crude oil data for the period January 2005 to November 2012. The results show that the data analyzed follows the ARIMA(1,2,1)-GARCH(0,3) model, and the crude oil price forecast for December 2012 is 105.5528 USD per barrel. The prediction results of crude oil prices are expected to be important information for all sectors related to crude oil.
Value-at-Risk Estimation Method Based on Normal Distribution, Logistics Distribution and Historical Simulation Susanti, Dwi; Sukono, Sukono; Verrany, Maria Jatu
Operations Research: International Conference Series Vol. 1 No. 1 (2020): Operations Research International Conference Series (ORICS), March 2020
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v1i1.19

Abstract

This paper discusses the risk analysis of single stock and portfolio returns. The stock data analyzed are BNI, BRI shares and portfolio. After obtaining a stock return, value at risk (VaR) will be estimated using the normal distribution approach, logistic distribution, and historical simulation. From the VaR results, a backtest is then conducted to test the validity of the model and the backtest results for BNI and the portfolio produce a smaller QPS on the historical simulation method compared to the normal distribution and logistics distribution approaches. This shows that BNI VaR and VaR portfolios with the historical simulation method are more consistent than other methods. While the backtest results for BRI produced the smallest QPS on the normal distribution approach compared to the logistical distribution and historical simulation approaches. This shows that the VaR BRI using the normal distribution approach is more consistent than the other methods.
Adomian Decomposition Method and The Other Integral Transform Sumiati, Ira; Sukono, Sukono
Operations Research: International Conference Series Vol. 1 No. 4 (2020): Operations Research International Conference Series (ORICS), December 2020
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v1i4.151

Abstract

The Adomian decomposition method is an iterative method that can be used to solve integral, differential, and integrodifferential equations. The differential equations that can be solved by this method can be of integer or fractional order, ordinary or partial, with initial or boundary value problems, with variable or constant coefficients, linear or nonlinear, homogeneous or nonhomogeneous. This method divides the equation into two forms, namely linear and nonlinear, so that it can solve equations without linearization, discretization, perturbation, or other restrictive assumptions. The basic concept of this method assumes that the solution can be decomposed into an infinite series. This method decomposes the nonlinear form (if any) of the equation with the Adomian polynomial series. This decomposition method can be combined with various integral transform, such as Laplace, Sumudu, Elzaki, and Mohand. The main idea of this technique assumes that the solution can be decomposed into an infinite series, then applies the integral transform to the differential equation. The main advantage of this technique is that the solution can be expressed as an infinite series that converges rapidly to the exact solution. This paper aims to combine the Adomian decomposition method with the new integral transform introduced by Kumar et al. (2022). This integral transform is called the Rishi transform. A scheme for solving fractional ordinary differential equations using the combined method is presented in this paper.
Analysis of the Effect of Temperature and Rainfall on Coffee Productivity in Indonesia using the Cobb-Douglas model for Determining Insurance Premiums Novianti, Saqila; Riaman, Riaman; 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.v2i3.179

Abstract

Coffee is one of Indonesia's foreign exchange earners and plays an important role in the development of the plantation industry. Indonesia is a coffee bean producing country ranked 4th in the world after Brazil, Vietnam, and Colombia. The agricultural sector in Indonesia has risks and uncertainties including a decrease in production yields which results result in a decrease in farmers income. The risk of loss in coffee is caused by temperature and rainfall. Efforts that can be made to reduce losses are through risk transfer through agricultural insurance. The purpose of this study to analyze the effect of temperature and rainfall on coffee productivity in Indonesia and determine the insurance premium. This research uses data on coffee productivity, temperature, and rainfall from 1980-2019. The relationship between coffee productivity as a dependent variable while temperature and rainfall as an independent variable was used the Cobb-Douglas method. The results that will be obtained from this study indicate the temperature and rainfall affect coffee productivity in Indonesia, and obtain insurance issued by the farmers to the insurance companies. The results obtained from the data analysis show that temperature and rainfall have an effect on coffee productivity in Indonesia. The results of productivity predictions are used as the basis for determining the price of insurance premiums issued bye insurance companies.
Prediction of the Number of Visitors to Tourism Objects in the Ujung Genteng Coastal Area of Sukabumi Using the Holt-Winter Method Salamiah, Mia; Sukono, Sukono; Djauhari, Eddy
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.v2i4.184

Abstract

Ujung Genteng Sukabumi Beach is one of the tourism destinations in Sukabumi Regency, West Java. Forecasting tourist arrivals is a very important factor for tourist destination policies and contributes to the regional economy and the surrounding community. The purpose of this study is to predict the number of tourists who come to Ujung Genteng Beach, Sukabumi. The method used is the Holt-Winter approach exponential smoothing. The Holt-Winter method is used for data that is not stationary, has both trend and seasonal elements. The Holt-Winters method has two models, namely the Additive model and the Multiplicative model. The data used is visitor data in January 2017 - February 2020, the results of the analysis show that the prediction of the number of visitors to Ujung Genteng beach in March 2020 from the additive model is 300 people with a MAPE value of 85.48% and an MSE value of 31230672.68 and a prediction of the number of beach visitors. Ujung Genteng in March 2020 from a multiplicative model of 740 people, with MAPE and MSE values obtained were 86.34% and 27754873.34.
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
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

Abstract

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.
Determination of Earthquake Insurance Premium Based on Great Physical and Economic Loss Using the Bayesian Method Rahman, Rezki Aulia; Subartini, Betty; Sukono, Sukono; Sampath, Sivaperumal
Operations Research: International Conference Series Vol. 4 No. 1 (2023): Operations Research International Conference Series (ORICS), March 2023
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v4i1.207

Abstract

Indonesia is an area prone to earthquakes because it is traversed by the meeting point of 3 tectonic plates, namely: the Indo-Australian plate, the Eurasian plate and the Pacific plate. An earthquake is an event where the earth vibrates due to a sudden restraint of energy in the earth which is characterized by the breaking of rock layers in the earth's crust. Almost all regions in Indonesia are at risk of being exposed to earthquakes. To anticipate the risk of natural disasters, earthquakes are advised to join the insurance program provided by the insurance company. This study aims to determine earthquake insurance premiums based on large physical and economic losses. The method used is the Bayesian method. This method produces each estimated loss value which is then used to calculate the combined estimated loss value. After that, the combined estimated loss value is used to calculate the premium value. The result of this research is the premium which is calculated based on the principle of expected value and standard deviation principle. The premium resulting from the expected value principle is lower than the premium resulting from the standard deviation principle.
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.
Prediction of Motor Vehicle Insurance Claims Using ARIMA-GARCH Models Susanti, Dwi; Maraya, Nisrina Salsabila; sukono, sukono; Saputra, Jumadil
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.v5i3.331

Abstract

Motorized vehicles are one of the means of transportation used by Indonesian people. As of 2021, the Central Statistics Agency (CSA) recorded the growth of motorized vehicles in Indonesia reaching 141,992,573 vehicles. Lack of control over the number of motorized vehicles results in losses for various parties, such as accidents, damage and other unwanted losses. The size of insurance claims has the potential to fluctuate, because it is influenced by several factors, such as policy changes, market conditions and economic conditions. This research aims to predict the size of motor vehicle insurance claims using the ARIMA-GARCH model which is used to predict the size of vehicle insurance claims by dealing with non-stationarity and heteroscedasticity in time series data. Based on research, the best model obtained is the ARIMA (2,1,3) - GARCH (1,0) model which produces seven significant parameters. Meanwhile, based on the MAPE value, it shows that the ARIMA (2,1,3)-GARCH (1,0) model is quite accurate. The results of this research can be taken into consideration in predicting the size of insurance claims in the future.
Co-Authors Abdul Talib Bon Abiodun Ezekiel Owoyemi Achmad Bachrudin Adhitya Ronnie Effendie, Adhitya Ronnie Agung Prabowo Agung Prabowo Agung Prabowo Agus Santoso Agus Santoso Agus Sugandha Agustini Tripena Br Surbakti Aisyah Nurul Aini Amalia, Hana Safrina Amitarwati, Diah Paramita Apipah Jahira, Juwita Asep K Supriatna Asep Saepulrohman Asep Solih Awalluddin, Asep Solih Asri Rula Hanifah Audina, Maudy Afifah Aulia Kirana Aziza Ayu Nurjannah Bakti Siregar Banowati, Puspa Dwi Ayu Basuki , Basuki Basuki Bayyinah, Ayyinah Nur Betty Subartini Bimasota Aji Pamungkas bin Mamat, Mustafa Budi Pratikno Candra Budi Wijaya Carissa, Katherine Liora Dara Selvi Mariani Dedy Rosadi Dedy Rosadi Dewi Ratnasari DEWI RATNASARI Dhika Surya Pangestu Diah Chaerani Diah Paramita Amitarwati Diana Ekanurnia Dianti, Estu Putri Dihna, Elza Rahma Dini Aulia Dwi Susanti Dwi Susanti Dwi Susanti Dwi Susanti Dwi Susanti Dwi Susanti Eddy Djauhari Edi Kurniadi Ema Carnia Emah Suryamah, Emah Eman Lesmana Endang Rusyaman Endang Soeryana Hasbullah Fasa, Rayyan Al Muddatstsir Febrianty, Popy Firdaus, Muhammad Rayhan Forman Ivana S. S. S. Ghazali, Puspa Liza Grida Saktian Laksito Hadiana, Asep Id Haq, Fadiah Hasna Nadiatul Hasbullah, Soeryana Hasriati Hasriati Hazelino Rafi Pradaswara Herlina Napitupulu Herlina Napitupulu Hidayana, Rizki Apriva Ibrahim M Sulaiman Ihda Hasbiyati Iin Irianingsih Ira Sumiati Ismail Bin Mohd Januaviani, Trisha Magdalena Adelheid Jumadil Saputra Jumadil Saputra Kahar, Ramadhina Hardiva kalfin Kalfin Kalfin, Kalfin Khairi, M. Ihsan Kusumaningtyas, Valentina Adimurti Labitta, Kirana Fara Laksito, Grida Saktian M. Ihsan Khairi Maraya, Nisrina Salsabila Maulana Malik Maulida, Ghafira Nur Ma’mur, Lutfi Praditia Melina Melina Melina Melina, Melina Mochamad Suyudi Mohamad Nurdin, Dadang Muhammad Arief Budiman Muhammad Iqbal Al-Banna Ismail Mustafa Mamat Mustafa Mamat Mustafa Mamat Mustafa Mamat Mustafa Mamat Nabilla, Ulya Nahda Nabiilah Nita Rulianah Noriszura Ismail Norizan Mohamed Novianti, Saqila Novieyanti, Lienda Novinta S, Fujika Novitasari, Ela Nugraha, Dwita Safira Nur Mahmudah Nurdyah, Himda Anataya Nurfadhlina Abdul Halim Nurul Fadilah Okta Yohandoko, Setyo Luthfi Pardede, Ester Priyatna, Yayat Puspa Liza Ghazali Putri, Aulya Putri, Linda Damayanti Putri, Sherina Anugerah Raharjanti, Amalia Rahman, Rezki Aulia Ramdhania, Tya Shafa Ratih Kusumadewi Riadi, Nadia Putri Riaman Riaman Riaman Riaman Riaman Riaman Riaman Riaman, Riaman Riaman, Riaman Rini Cahyandari Riza Adrian Ibrahim Rosadi, D. - Rulianah, Nita Saefullah, Rifki Salamiah, Mia Salih, Yasir Sampath, Sivaperumal Saputra, Jumadil Shindi Adha Gusliana Sianturi, Sri Novi Elizabeth Sisilia Sylviani Siti Sabariah Abas Soeryana Hasbullah Sri Purwani Stanley Pandu Dewanto Subanar - Subanar . Subanar Subanar Subiyanto Subiyanto Sudradjat Supian Suhaimi, Nurnisaa binti Abdullah Sulastri, S Sumiati, Ira Supian, Sudradjat Supriyanto Supriyanto Suroto Suroto Susanto, Sunarta Sutiono Mahdi Sutisna, Sarah Suyudi, Mochamad Suyudi, Mochammad T.P Nababan Tampubolon, Carlos Naek Tua Tika Fauzia Tiswaya, Waway Titi Purwandari Titin Herawati Umar A Omesa Valentina Adimurti Kusumaningtyas Verrany, Maria Jatu Vimelia, Willen Wahid, Alim Jaizul Wan Muhamad Amir W Ahmad Widyani, Azizah Rini Wiliya Wiliya Yasir Salih Yasmin, Arla Aglia Yhenis Apriliana Yulianus Brahmantyo Yulison Herry Chrisnanto Yuningsih, Siti Hadiaty Yuyun Hidayat Zahra, Ami Emelia Putri Zinedine Amalia Noor Mauludy Reihan