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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 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 Mathematical Sciences and Applications Journal International Journal of Technology and Education Research
Sukono .
Department Of Mathematics, Faculty Of Mathematics And Natural Sciences, Universitas Padjadjaran
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An Empirical Research of Critical Incident of Earthquake Disaster Basedon Credible Association Data Mining Suyudi, Mochamad; Sukono, Sukono
International Journal of Global Operations Research Vol. 2 No. 1 (2021): International Journal of Global Operations Research (IJGOR), February 2021
Publisher : iora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/ijgor.v2i1.65

Abstract

Earthquake disasters usually cause panic in the community affected areas, so it is necessary to be analyzed to deal with earthquake events in the future. This paper analyzes data from 9 major earthquakes in Indonesia over the past 4 years and determines 14 critical events. The analysis is based on credible association rules (CAR), data mining, and the maximum clique algorithm. To verify the accuracy of the association relationship and CAR effectiveness, it is performed using a maximum clique algorithm. Based on the results of data mining, that earthquakes have a credible association relationship and have a probability of critical events in various regions in Indonesia. Thus, these results can be used for prediction, early warning, and logistic distribution planning.
Application of Structural Equation Model to Analyze Factors Affecting Financial Planning After Retirement Khairi, M. Ihsan; Susanti, Dwi; Sukono, Sukono
International Journal of Global Operations Research Vol. 2 No. 3 (2021): International Journal of Global Operations Research (IJGOR), August 2021
Publisher : iora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/ijgor.v2i3.87

Abstract

Retirement is something that every working individual will experience. Retirement according to the Big Indonesian Dictionary (KBBI) is not working anymore because the term of office has finished. A person who has retired usually has the right to a pension fund. After retirement, the individual's income will decrease, but the necessities of life can increase. In order to still be able to meet the needs of life after retirement, it is necessary to have financial planning after retirement. There are several factors that influence financial planning after retirement, including income, attitude and culture. Income is an important issue in financial planning. One thing to consider carefully when planning for retirement and setting aside funds for that purpose is the estimate of the amount of money needed to have the expected quality of life in retirement. Attitude towards retirement planning is an internal psychological condition that is influenced by positive or negative assessments related to retirement planning. Cultural differences will result in different financial plans between individuals. In this study, the Structural Equation Model will be used to analyze the factors that influence financial planning after retirement for teachers in several schools in Tanah Datar Regency, West Sumatra. This study uses quantitative methods using a questionnaire as a data collection tool. Based on the collected questionnaires, simulations were carried out to obtain 170 data randomly. To facilitate data analysis, the AMOS application will be used. The results showed that these three factors had a significant effect on financial planning after retirement. The most influential factor on financial planning after retirement is culture with a parameter value of 0.639.
Determination of the Contribution of the Reserve Fund for Flood Natural Disaster Management in the DKI Jakarta Region Nugraha, Dwita Safira; Susanti, Dwi; Sukono, Sukono
International Journal of Global Operations Research Vol. 2 No. 4 (2021): International Journal of Global Operations Research (IJGOR), November 2021
Publisher : iora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/ijgor.v2i4.88

Abstract

Floods are natural disasters that are quite difficult to predict. As a result, there are many losses both materially, morally and even to the point of taking lives. In Indonesia, one of the areas that experience flooding the most is DKI Jakarta. In early 2020, flooding was the biggest cause of loss in the region. The role of the people of DKI Jakarta is very important in collecting contributions to the reserve fund for disaster emergency response. Therefore, this study aims to estimate the amount of reserve fund contributions for community-based flood disaster management in the DKI Jakarta area based on the Collective Risk Model method approach, using Poisson and Log-Normal distributions, including parameter estimates  and (μ,σ) , resulting in an estimate of the expected magnitude of the risk of loss. Based on these expectations, the contribution amount can be calculated using the Individual and Collective Risk Model. The result of this research is the contribution of funds which is calculated based on the principle of expected value
Risk Analysis on Foreign Exchange Using Value-at-Risk Parametric Approach Susanto, Sunarta; Riaman, Riaman; 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.v3i4.190

Abstract

Foreign Exchange or usually known as Forex are one of the most famous investment objects. When investing in Forex, it is necessary to know the movements of the foreign exchange price as well as the risk that might happen. The purpose of this study is to predict the level of risk, seeing the characteristics of foreign exchange, and compare which foreign exchange is better to invest in. The Value-At-Risk (VaR) models used to predict the risk of the foreign exchange are VaR of standard normal distribution approach, VaR of Student-t distribution approach, and Modified VaR normal. Based on the research, the potential loss for AUD is Rp 9,445.26, CAD is Rp 7,972.62, CHF is Rp 7,073.74, EUR is Rp 6281.90, GBP is Rp 9,234.37, JPY is Rp 10,971.68, SGD is Rp 3,988.65, and USD is Rp 2,896.47 with an assumption that an investor invests as much as Rp 1,000,000.00 to each foreign exchange. USD is the best foreign exchange to choose because it has the lowest potential risk based on its VaR.
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
Application of Black Scholes Method for Determining Agricultural Insurance Premiums Based on the Rainfall Index Using the Historical Burn Analysis Method Zahra, Ami Emelia Putri; Riaman, Riaman; Sukono, Sukono
International Journal of Global Operations Research Vol. 4 No. 1 (2023): International Journal of Global Operations Research (IJGOR), February 2023
Publisher : iora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/ijgor.v4i1.209

Abstract

Indonesia is a tropical area where it often rains. Uncertain rainfall conditions can have an impact in the form of losses in agriculture, including for rice farmers. The total rice productivity in Indonesia, one of which is in Majalengka Regency, is thought to be quite high, so the losses will be significant. Therefore, it is necessary to make efforts to reduce the impact of losses experienced by farmers, one of which is through insurance programs in the agricultural sector. Rainfall index-based agricultural insurance provides protection to farmers in the form of capital assistance in the event of crop damage resulting in crop failure due to erratic rainfall. This study aims to calculate the agricultural insurance premium based on the rainfall index. The method used to calculate the premium is the Black-Scholes method, while the Historical Burn Analysis method is used to determine the rainfall index. The data used is rainfall data in Majalengka Regency in 2014–2021. The results showed that the premium price in Majalengka Regency depends on the value of the trigger obtained, with a price range between IDR 1,089,646.39 and IDR 1,266,213.02.
Determination of Credit Insurance Premium Due to Default Using the Black-Scholes-Merton Model Ramdhania, Tya Shafa; Riaman, Riaman; Sukono, Sukono
International Journal of Global Operations Research Vol. 4 No. 1 (2023): International Journal of Global Operations Research (IJGOR), February 2023
Publisher : iora

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47194/ijgor.v4i1.210

Abstract

Banks are vulnerable to the risk of bad credit or default because customers are unable to pay their debts. Risks that may occur in the future can be in the form of unexpected events and can be experienced by anyone, causing the loan to not be fully repaid. Therefore, it is necessary to have insurance to overcome risks due to default in protecting oneself from the risk of unexpected events, namely credit insurance. This study aims to calculate the premium price using the Black-Scholes-Merton model approach. The data used is arrears data of customers PD. Bank Perkreditan Rakyat (BPR) Artha Sukapura in 2003-2020. The data is compiled into a cumulative relative frequency distribution table, resulting in a number of random numbers. Based on the cumulative relative frequency distribution table, data simulation was determined using Monte Carlo. Based on the results of the analysis, the simulation data obtained by the standard deviation are relatively stable and lognormal distributed. Then pricing is done to determine the premium price from the sample data. From the results of the calculations in this study, a premium value of  was obtained for arrears of  with a loan of .
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.
Mean-Variance Optimal Portfolio Selection with Risk Aversion on Transportation and Logistics Sector Stocks Based on Multi-Criteria Decision-Making Putri, Aulya; Riaman, Riaman; 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.v6i1.895

Abstract

The importance of the transportation and logistics sector to a country's economy, coupled with the growth of this sector in Indonesia, requires investment support for this sector to continue to grow. Therefore, stocks in the transportation and logistics sector are attractive for investment portfolio consideration. The optimal portfolio selection is to minimize the risk with the expected return. In the formation of an investment portfolio, the problem is how to determine the weight of capital allocation in order to get the maximum return while still considering the risk in each stock, by considering several criteria in decision making. This study was conducted to determine the best stock selection in the transportation and logistics sector listed on the Indonesia Stock Exchange, and determine the optimal weight in the investment portfolio. The method used is Multi-Criteria Decision Making (MCDM), namely Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) using 15 financial metrics as relevant criteria in stock selection. Furthermore, to determine the allocation weight to form an optimal stock portfolio using the Mean-Variance model with Risk Aversion. The stocks analyzed were 28 stocks in the transportation and logistics sector. The results of research based on MCDM selected 9 stocks, namely MITI, BIRD, HATM, TMAS, JAYA, PPGL, BPTR, ASSA, and RCCC. However, TMAS, PPGL, and BPTR stocks are not included in portfolio formation because they have a negative average return. Based on the optimization results, the allocation weights of the 6 stocks included in the optimal portfolio are BIRD (37.7%), JAYA (24.6%), MITI (12.9%), HATM (9.9%), ASSA (7.5%), and RCCC (7.4%). The results of this study are expected to be a consideration in making investment decisions.
Co-Authors Abdul Talib Bon Abiodun Ezekiel Owoyemi Achmad Bachrudin Adhitya Ronnie Effendie, Adhitya Ronnie Agung Prabowo Agung Prabowo Agung Prabowo Agung, Moch Panji 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 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 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 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 Rini Cahyandari Riza Adrian Ibrahim Rosadi, D. - Rulianah, Nita Salamiah, Mia Salih, Yasir Sampath, Sivaperumal Saputra, Jumadil 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 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