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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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Identifying Unwanted Conditions Using Lower Boundaries on Individual Control Charts in the Context of Supply Chain Economic Resilience of Cities in Indonesia Purwandari, Titi; Sukono, Sukono; Hidayat, Yuyun; Ahmad, Wan Muhamad Amir W
International Journal of Supply Chain Management Vol 9, No 5 (2020): International Journal of Supply Chain Management (IJSCM)
Publisher : ExcelingTech

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59160/ijscm.v9i5.5346

Abstract

This study presents the unwanted conditions determination. The economic resilience model without taking into account the level of disruption and unwanted conditions is unrealistic model. The Objective is to determine unwanted conditions as a key criterion in determining the economic resilience status of a city. This study used data on Concern variables group and Control variables groups from website of Central Bureau of Statistics Indonesia. These data covered all 514 cities in Indonesia and are observed for a 5-year period from 2014 to 2018. The data is useful to develop a statistical model that can explain well the pattern of relationships between concern variables and control variables. Piecewise linear regression is applied to identify statistics model between Pc and Z, Lower Control Limit (LCL) for variable Z using Individual control Chart is applied to determine the unwanted conditions.  We obtained that the control variable, Z is the ratio between the original income of the region (PAD) with the number of poor people in a city and the concern variable is income per capita, Pc of a city. Piecewise linear regression with breakpoint 126,255,066 can explain well the pattern of relationships between Z and Pc variables. The equation is: Pc = 26,660,263+0.28Z, R-square = 70.48%. LCL value is.1.884.059.5 so all cities that have a Z value below 1.884.059.5 fall into the unwanted condition area and after careful examination is obtained percentage of cities classified as do not have economic resilience , PER =28%. Cities that fall into unwanted conditions are defined as cities that cannot bear receiving economic shocks.
Supply Chain Management of Operational Value-at-Risk for Estimating the Maximum Claims Potential of House Fire Risk Using a Portfolio Approach Hasbullah, Endang Soeryana; Sukono, Sukono; Suyudi, Mochammad; Agung, Moch Panji; Saepulrohman, Asep
International Journal of Supply Chain Management Vol 9, No 5 (2020): International Journal of Supply Chain Management (IJSCM)
Publisher : ExcelingTech

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59160/ijscm.v9i5.4561

Abstract

The occurrence of house fires in densely populated areas has a high-risk level. One of city in Indonesia that has high-risk level of this incident is Bandung City. That high-risk incident cause anxiety community, and also cause many house fire insurance product arise. Insurance product is made to protect consumers from risk and guarantee by a premium. Insurance company formulate premium based on analysis calculation from expected claim, cost, commission, and margin. This paper aims to estimate maximum expected claim using portfolio approach. There are several steps in this research. The first step is resampling the data used Maximum Entropy Bootstrapping (ME Boot). Next, determine threshold value to get extreme data value. Then, conduct Kolmogorov-Smirnov test to fit the data with Generalized Pareto Distribution (GPD). Afterwards, estimate Generalized Pareto Distribution (GPD) parameter. Then, calculate Operational Value-at-Risk (OpVaR Portfolio) as maximum expected claim measurement. The results from this research are the expected maximum claim of IDR. 18.690.352.676,615 for next one year with 95% confidence level. The expected claim result could be used as consideration for house fire insurance products premium that appropriate for Bandung City community.
Determining Premium for Disaster Reinsurance Program through Supply Chain Risk Management: An Application of Peak Over Threshold (POT) Approach Sukono, Sukono; Subartini, Betty; Napitupulu, Herlina; Novitasari, Ela; Santoso, Agus; Ghazali, Puspa Liza; Saputra, Jumadil
International Journal of Supply Chain Management Vol 9, No 5 (2020): International Journal of Supply Chain Management (IJSCM)
Publisher : ExcelingTech

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59160/ijscm.v9i5.4305

Abstract

The purpose of this study is to determine the pricing (premium) for disaster reinsurance program. For those, this study uses the Peak Over Threshold (POT) approach, where the method pays attention to the pattern of heavy tail behaviour on the number of victims killed due to disaster events through extreme values with a reference value called the threshold u. The results of the analysis showed that the reinsurance premiums for flood disaster per year that must be paid by insurance company is IDR 712,008,900.50 with the maximum amount of reinsurance risk, L is IDR20,000,000,000.00, the insurance company retention, S is IDR200,000,000.00, the sensitivity minimum number of victims in one disaster event  with 5 people. In conclusion, the reinsurance premium per year that must be paid by insurance companies to reinsurance companies will be increasing when the insurance company retention S is smaller, the maximum amount of risk covered by reinsurance L is greater, and the number of victims died u decreases.
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.
Exploring Investment Decision-Making with CAPM: Case Studies on Ten Raw Materials Companies Listed in Stock Exchange Haq, Fadiah Hasna Nadiatul; Sukono, Sukono
Operations Research: International Conference Series Vol. 5 No. 1 (2024): Operations Research International Conference Series (ORICS), March 2024
Publisher : Indonesian Operations Research Association (IORA)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/orics.v5i1.294

Abstract

The investment business in Indonesia experienced significant growth in line with the increasing stock trading activity in the capital market. The large number of capital markets in Indonesia means investors have to be careful in determining the shares to be chosen. Based on transaction value, the raw materials sector is the second largest sector that supports the Indonesian capital market. Given the large number of issuers in the raw materials sector, determining investment portfolios is important to obtain optimal results. CAPM can classify stocks as efficient or not based on their expected return value. The results obtained can be used as a consideration in portfolio decision-making. This research identifies 10 stocks in the raw materials sector listed on the IDX. Of the 10 stocks studied, 8 are included in the efficient category, which has a greater return than expected, and 2 are included in the inefficient category. This means that investors who want to invest in raw materials can make a decision to buy these 8 stocks, and it is not recommended to buy shares in 2 inefficient category stocks or sell 2 stocks.
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

Abstract

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.
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.
Forecasting Indonesian Stock Index Using ARMA-GARCH Model Susanti, Dwi; Labitta, Kirana Fara; 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.v5i3.328

Abstract

The stock market is an institution that provides a facility for buying and selling stocks. Covid-19 is an issue that has affected the stock markets of many countries, including Indonesia. Due to the pandemic, the condition of stocks before and during Covid-19 is certainly different. Stocks can be measured using stock indices. To predict future stock conditions, it is necessary to forecast the stock index. Therefore, this research aims to forecast the Indonesian stock index before and during Covid-19 using the ARMA-GARCH time series model. The results show that the best forecasting model for before Covid-19 data is ARMA(0,2)-GARCH(1,0), and for the data during Covid-19, it is ARMA(3,3)-GARCH(3,3). These findings can help investors make better investment decisions in the future.
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.
Application of the AHP-TOPSIS Method to Support Stock Investment Decisions Based on Financial Ratio Analysis Pardede, Ester; Susanti, Dwi; Sukono, Sukono
International Journal of Global Operations Research Vol. 4 No. 4 (2023): International Journal of Global Operations Research (IJGOR), Nopember 2023
Publisher : iora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/ijgor.v4i4.260

Abstract

Stock is one form of investment that is currently popular, both for young people, parents, and industry. This can be seen from the increasing number of investors and companies listed on the Indonesia Stock Exchange (IDX). This makes investors confused in determining the best stock choices. Analysis of stock selection needs to be done before someone invest so that the selected stock does not lose and can generate optimal profits. This study discusses the recommendation for alternative stocks from the IDX30 index. The parameters for selecting alternative stocks considered include the criteria of Earning Per Share (EPS), Return on Assets (ROA), Return on Equity (ROE), and Net Profit Margin (NPM). Then the weight of each criterion will be searched using the Analytical Hierarchy Process (AHP) method and sorted using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method to produce stock recommendations from companies listed on the Indonesia Stock Exchange. The results showed that the Earning Per Share (EPS) criteria became the first priority with a weight of 0,2927, then Return on Equity (ROE) with a weight of 0,2728, followed by Net Profit Margin (NPM) with a weight of 0,2583, and Return on Assets (ROA) with a weight 0,1759. Then alternative results are obtained based on the preference value and ranking 14 companies that have a preference value above 0.5 and can be used as a consideration in making investment decisions, with BBCA as a priority alternative.
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