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Investment Portfolio Optimization Using Genetic Algorithm on Infrastructure Sector Stocks Based on the Single Index Model Bayyinah, Ayyinah Nur; Riaman, Riaman; Sukono, Sukono
International Journal of Quantitative Research and Modeling Vol 6, No 2 (2025)
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v6i2.977

Abstract

Investment is a strategic step in managing assets to gain profits in the future by allocating some funds in the present. However, behind the promising potential returns, investment also contains risks that cannot be ignored. One way to reduce the level of risk in investing is to implement a portfolio diversification strategy, which is to form an optimal portfolio by allocating investments to various stocks. This study aims to identify the stocks that form the optimal portfolio, determine the optimal weight of each stock, and calculate the expected return and risk of the portfolio. The portfolio optimization process is carried out using Genetic Algorithm, with the calculation of expected return and risk using the Single Index Model (SIM) approach. The data used includes data on stocks in the infrastructure sector for the period July 1, 2023 to June 30, 2024. The results showed that there were six stocks selected in forming the optimal portfolio with the weight of each stock: PGEO 15.0023%, ISAT 32.1522%, GMFI 4.7822%, EXCL 15.3236%, JSMR 29.7379, and OASA 3.0018%. This optimal portfolio provides an expected return of 0.1167% with a portfolio risk of 0.0152%.
Sustainable Cultural Tourism Development Strategy in Karuhun Eco Park Village, Sumedang Regency, West Java, Indonesia Ratnasari, Dewi; Tiswaya, Waway; Riaman, Riaman; Sukono, Sukono; Hidayana, Rizki Apriva; Laksito, Grida Saktian
International Journal of Business, Economics, and Social Development Vol. 6 No. 3 (2025)
Publisher : Rescollacom (Research Collaborations Community)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijbesd.v6i3.989

Abstract

The development of cultural arts tourism as a sustainable tourism destination is a priority considering the features and nature of these locations, which highlight a number of elements such the local economy, environment, culture, preservation, and community empowerment. One of the cultural tourism areas in Indonesia, to be precise the province of West Java, namely Kampung Ladang in Sumedang Regency which is located at the top of Pasir Peti hill - Marga Laksana Sumedang Village. Kampung Ladang is one of Sumedang's cultural tourism centres by collaborating with the local community to maintain and preserve traditional Sundanese culture and procedures, especially Sumedang culture and traditions. This research uses qualitative methods and uses IFAS / EFAS and SWOT Analysis which aims to identify the potentials developed by Kampung Ladang with data collection carried out by observation, indepth interviews, and documentaries. The results of this study indicate that Kampung Ladang has three potentials that are ready to be developed in attracting tourists to visit such as potentials that need to be improved, namely attractions and activities, external supporting potentials, namely accessibility infrastructure consisting of information boards and other supporting facilities, and potentials that are not yet available, namely the provision of tour packages through marketing and promotion strategies that can attract tourists to visit and can develop community-based sustainable tourism that is community-centred to improve community welfare, besides that government support is needed in carrying out development and maintenance. In order to meet the needs of travellers, businesses, the environment, and tourism management communities, among other stakeholders, sustainable tourism management is a type of tourism management that will play a significant role in both the present and the future economic and social conditions.
Mathematical Model of Paddy Production using Cobb Douglas Method Based On Weather Factors Riaman, Riaman; Parmikanti, Kankan; Subartiny, Betty; Supian, Sudradjat
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 7, No 4 (2023): October
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v7i4.15446

Abstract

This research was conducted to model paddy production based on weather factors. This needs to be done to predict crop yields and regulate paddy cropping patterns. In setting the cropping pattern, the weather is selected which consists of temperature, wind speed, and rainfall, as a variable factor of production. Meanwhile, other factors (such as fertilization, sunshine, air humidity, etc.) are assumed to be in catteries paribus conditions. The research method used is a mixed method between qualitative methods which are descriptive details and quantitative methods which are based on weather data and Paddy's harvest data. The aim of this research is to analyze the influence of weather on paddy production results. Analysis is done to get the production function. Parameters are estimated using the Ordinary Least Square (OLS) method by minimizing the sum of squared errors. Based on data analysis, a correlation of 0.899 was obtained with a standard error of .051665515. the results of model testing also show significant results with the F statistic obtained at 33.98 with a p-value of 0.028 which is less than 5%. So it can be concluded that there is a significant relationship between weather and paddy productivity. In such a way that the weather can be used as a reference in determining the prediction of loss risk and paddy production. This model can also be recommended for further research, namely to determine insurance losses that may arise when extreme weather events occur. 
A Systematic Literature Review on Mean-CVaR Based Financial Asset Portfolio Weight Allocation Using K-Means Clustering Wahid, Alim Jaizul; Riaman, Riaman; Sukono, Sukono
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 10, No 2 (2025): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v10i2.36590

Abstract

This study aims to identify and analyze the application of the Mean-Conditional Value-at-Risk (Mean-CVaR) model in the allocation of financial asset portfolio weights combined with the K-Means Clustering algorithm. The Systematic Literature Review (SLR) method is used with the PRISMA protocol through the stages of identification, screening, eligibility, and inclusion. Data is obtained from Scopus, ScienceDirect, and Dimensions databases, then selected up to six relevant primary articles. The results of the study indicate that CVaR is the dominant risk measure in portfolio optimization, while K-Means Clustering serves as a method of grouping assets to increase diversification. The optimization methods used include Genetic Algorithm, Particle Swarm Optimization, Teaching Learning-Based Optimization, and Stochastic Programming. However, direct integration between Mean-CVaR and K-Means within a portfolio weight allocation framework is still rare. This research emphasizes the need to develop a hybrid model that combines both approaches in an integrated manner, applied to a multi-asset portfolio, and validated under various market conditions to produce an optimal, adaptive, and resilient investment strategy against extreme risks.
Calculation of Rice Farming Insurance Premium Price in Magelang City Based on Rainfall Index with Black-Scholes Method Raharjanti, Amalia; Riaman, Riaman; Sukono, Sukono
International Journal of Business, Economics, and Social Development Vol. 5 No. 1 (2024)
Publisher : Rescollacom (Research Collaborations Community)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijbesd.v5i1.581

Abstract

Indonesia is a country with two seasons, the rainy season and the dry season. Unstable rainfall can affect rice production and may cause crop failure. The amount of rice production in Indonesia, one of which is in Magelang City, is quite large, so the losses that may be experienced are quite significant. Therefore, a way to reduce the impact of losses experienced by farmers is needed, one of which is through the rice farming insurance program. The purpose of this study is to determine the premium price of rice farming insurance based on rainfall index based on the exit value and trigger value in each growing season. Insurance using the rainfall index can provide protection to farmers due to too little rainfall or too much rainfall. Too much rainfall can cause damage to rice plants resulting in crop failure. The premium calculation method uses the Black-Scholes principle, while the exit value and trigger value are determined by the Historical Burn Analysis method. The result of this study is to obtain various trigger values and exit values as well as premiums that must be paid by farmers in each normal, high, and low (dry) rainfall condition. This value determines the premium price obtained for normal rainfall which is IDR 735,739.66 to IDR 871,698.64, for high rainfall the premium price obtained is IDR 1,404,184.75 to IDR 1,643,307.75, and for low rainfall (dry season) it is IDR 5,541,806.10 to IDR 6,689,629.88. 
Investment Portfolio Optimization Using Black-Litterman Model in Smart Carbon Economy Transition Kahar, Ramadhina Hardiva; Riaman, Riaman; Sukono, Sukono
International Journal of Business, Economics, and Social Development Vol. 5 No. 1 (2024)
Publisher : Rescollacom (Research Collaborations Community)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijbesd.v5i1.582

Abstract

An optimal investment portfolio needs to be formed before an investor invests because it can help investors determine which financial instruments are suitable to choose in order to get the maximum return or profit and the minimum level of risk. In the current situation, where there is an economic transition to a smart carbon economy or low carbon economy, it is necessary to form the optimal portfolio of stocks to facilitate investors in making investments. The purpose of this study is to form the optimal investment portfolio using the Black-Litterman model in a smart carbon economy. The data used is stock data from 24 companies listed on the LQ45 Low Carbon Leaders index for the period 2022-2023. Based on the research results, the Black-Litterman model generates the optimal portfolio with a 0.1% expected return. Thus, the optimal portfolio results with the Black-Litterman model are estimated to generate a profit of 0.1% for smart carbon stock data listed on the LQ45 Low Carbon Leaders index for the 2022-2023 period.
Determination of Optimal Stock Portfolio Return by Single Index Model (Case Study on Banking Sector Stocks in Indonesia) Rahmawati, Septi; Susanti, Dwi; Riaman, Riaman
International Journal of Business, Economics, and Social Development Vol. 5 No. 1 (2024)
Publisher : Rescollacom (Research Collaborations Community)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijbesd.v5i1.585

Abstract

The optimal portfolio is a portfolio chosen by investors from the many options available in the collection of efficient portfolios. To get the optimal proportion, which is the maximum return and minimum risk, it is necessary to analyze the stocks to be selected in the investment model. The research objective is to determine the optimal return, risk, and proportion for each banking stock portfolio in Indonesia in the period February - July 2023. The method used is the Single Index Model. The process of determining the optimal proportion of stocks with the Single Index Model requires stock and market return data as the main basis for applying this method. This study involves the formation of an optimal portfolio of daily closing prices of 46 banking stocks.  As a result of this research, there are 5 optimal stocks that meet the criteria for optimal portfolio formation with each fund proportion of 21.43% (BNII), 13.52% (BDMN), 35.02% (BBRI), 23.69% (BTPN), and 6.34% (BBCA).  Expected return from optimal stocks is 0.152% and the risk that will be borne by investors is 0.0011% per day.
Mean-Variance Portfolio Optimization with Lot Size Constraints in Energy Stocks: A Monte CarloApproach Vimelia, Willen; Riaman, Riaman; Sukono, Sukono
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 10, No 1 (2025): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v10i1.32159

Abstract

Stock investment requires portfolio optimization strategies that maximize returns and consider risks and practical constraints, such as target lot sizes. These constraints are crucial to ensuring the realistic implementation of portfolios in compliance with market regulations, particularly in Indonesia, where 1 lot equals 100 shares. However, existing research on the Mean-Variance model and Monte Carlo simulation has rarely incorporated target lot constraints, limiting the applicability of these models in real-world scenarios. To bridge this gap, this study conducts a systematic literature review (SLR) on portfolio optimization in Indonesia's energy sector stocks, focusing on the Mean-Variance model, risk aversion, Monte Carlo simulation, and target lot constraints. The PRISMA framework guides this SLR, with bibliometric analysis performed using RStudio. A rigorous selection process from Scopus and ScienceDirect databases yielded 13 relevant articles for in-depth analysis creates a more practical and effective approach to portfolio management. This advancement enables investors to achieve balanced portfolios that are both theoretically robust and feasible in practice. The study contributes significantly to optimizing investment strategies for Indonesia’s energy sector and opens avenues for further research into practical portfolio optimization methods.
Optimization Modeling of Investment Portfolios Using The Mean-VaR Method with Target Return and ARIMA-GARCH Yasmin, Arla Aglia; Riaman, Riaman; Sukono, Sukono
CAUCHY: Jurnal Matematika Murni dan Aplikasi Vol 10, No 1 (2025): CAUCHY: JURNAL MATEMATIKA MURNI DAN APLIKASI
Publisher : Mathematics Department, Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/cauchy.v10i1.30042

Abstract

This research develops a portfolio optimization model using the Mean-Value at Risk (Mean-VaR) approach with a target return constraint, addressing the gap in models that specific return objectives. The ARIMA-GARCH model is utilized to predict stock returns and volatility, offering precise inputs for optimization. By applying the Lagrange method and Kuhn-Tucker conditions, the model determines optimal portfolio weights that balance risk and return. Using data from infrastructure stocks on the Indonesia Stock Exchange (January 2019-September 2024), the model’s effectiveness is validated through numerical simulations. The results illustrate efficient frontiers for target returns of 5x10^-6, 0.001, and 0.0019, revealing that higher return targets proportionally increase risk. ARIMA-GACRH’s advantage lies in its ability to capture both mean and variance dynamics, ensuring reliable volatility estimates for informed decision-making. This study contributes to portfolio optimization literature by emphasizing target return constraints and demonstrating the practical utility of volatility modeling. The findings provide a robust framework for investors to align portfolios with financial goals and risk tolerance. Future work could explore broader market contexts or integrated additional constraints for enhanced applicability.
Application of Historical Burn Analysis Method in Determining Agricultural Premium Based on Climate Index Using Black Scholes Method Ariyanti, Devi; Riaman, Riaman; Irianingsih, Iin
JTAM (Jurnal Teori dan Aplikasi Matematika) Vol 4, No 1 (2020): April
Publisher : Universitas Muhammadiyah Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.31764/jtam.v4i1.1799

Abstract

Farmers often suffer losses due to crop failure. The failure of the harvest is influenced by one of them is flooding, especially in Bandung which is quite frequent rain. Therefore one of the government's efforts to minimize losses from crop failures is the existence of an agricultural insurance program. The insurance system used is climate index insurance where the climate index is not plant insurance. This study aims to get a large premium to be paid by farmers using the Black-Scholes method. Meanwhile, to determine the climate index using the Historical Burn Analysis method. The results of this study are getting a variety of trigger values and exit values as well as the amount of premium that must be paid by farmers every planting season. Trigger values represent the minimum full payment limit. The exit value represents the maximum limit for no payment. The premium value obtained based on the selected trigger value also varies and is large enough so that it can be considered by farmers in choosing an agricultural insurance policy. Therefore, the method used must still be investigated to adjust to farmers, especially in Bandung.
Co-Authors AGUS SUPRIATNA Aldino Reisnanda Alit Kartiwa Anang Muhajirin Andhita Zahira Adib Annisa Aprillia Ariyanti, Devi Arla Aglia Yasmin Ary Robayani Asthie Zaskia Maharani Atha Hukama Aulianda Anisa Putri S. R. Aulya Putri Ayyinah Nur Bayyinah Azizah Rini Widyani Bayyinah, Ayyinah Nur Betty Subartini Betty Subartini Betty Subartini Betty Subartini Dewi Ratnasari Dwi Susanti Dwi Susanti Dwi Susanti Dwi Susanti Dwi Susanti Dwi Susanti Edi Kurniadi Emmanuel Parulian Sirait Estu Putri Dianti Ghazali, Puspa Liza Hasbullah, Soeryana Herlina Napitupulu Hidayana, Rizki Apriva Hukama, Atha Iin Irianingsih Jumadil Saputra Kahar, Ramadhina Hardiva kalfin Kalfin Kankan Parmikanti Khalilah Razanah Zakirah Komar Komar Laksito, Grida Saktian Linda Damayanti Putri Luki Setiawan Luki Setiawan Lutfi Praditia Ma’mur Maharani, Asthie Zaskia Ma’mur, Lutfi Praditia MIFTAAHUL JANNAH Moisino, Misel Lindi Nahda Nabiilah Noriszura Ismail Novianti, Saqila Pramudhita, Annisa Pryimak, Evgen Putri Adhira Novalia Putri Chaerunnisa Febryanti Putri, Aulya Putri, Linda Damayanti Qurrotu Aini Radya Pratiwi Serila Raharjanti, Amalia RAHMAWATI, SEPTI Ramdhania, Tya Shafa Ratih Kusumadewi Riadi, Nadia Putri Riza Adrian Ibrahim Saefullah, Rifki Silvia Wijaya Soeryana Hasbullah Subartiny, Betty Sudartianto Sudartianto Sukono Sukono Supian, Sudradjat Susanto, Sunarta Sya’imaa.HS, Audrey Ariij Tika Fauzia Tyrenia Rahmawati Ulfatmi, Ristifani Vimelia, Willen Wahid, Alim Jaizul Waway Tiswaya Widyani, Azizah Rini Willen Vimelia Yasir Salih Yasmin, Arla Aglia Yeremia Herry Parulian Yeremia Herry Parulian, Yeremia Herry Yudhi Andriyana Yulianus Brahmantyo Zahra, Ami Emelia Putri