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All Journal International Journal of Business, Economics, and Social Development International Journal of Research in Community Services International Journal of Quantitative Research and Modeling
Rizki Apriva Hidayana
Department of Mathematics, Faculty of Mathematics and Natural Sciences, National University of the Republic of Indonesia, Bandung, Indonesia
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Languange, Linguistic, Communication & Media Physics Social Sciences Other

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Implementation of Ruin Probability Model in Life Insurance Risk Management Nestia Lianingsih; Rizki Apriva Hidayana; Moch Panji Agung Saputra
International Journal of Quantitative Research and Modeling Vol. 5 No. 4 (2024): International Journal of Quantitative Research and Modeling
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v5i4.816

Abstract

This study examines the implementation of the ruin probability model in risk management in life insurance companies. The main focus of this study is to evaluate how factors such as initial surplus, premium revenue level, and claim frequency affect the ruin probability of insurance companies. Using the collective risk model approach and relevant claim distribution, this study develops two methods to calculate the ruin probability: an analytical approach and a Monte Carlo simulation. The simulation results show that increasing the initial surplus and premium level significantly reduces the ruin risk, while increasing the claim frequency increases the ruin probability. In addition, the gamma claim distribution is more suitable for modeling claims in life insurance than the exponential distribution. Model validation is carried out by comparing the prediction results with historical data of insurance companies, which shows a high level of accuracy. This study provides important insights for insurance companies in designing more effective and optimal risk management strategies.
Optimization Model in Transportation Based on Linear Programming Angellyca Leoni Manuela; Reivani Putri Berlinda Harahap; Tina Yoefitri; Nicko Meizani; Rizki Apriva Hidayana
International Journal of Quantitative Research and Modeling Vol. 6 No. 2 (2025): International Journal of Quantitative Research and Modeling
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v6i2.1018

Abstract

This study discusses the development of optimization models in transportation costs and routes and resource distribution based on Linear programming using various methods. This study aims to improve logistics efficiency, maximize the utilization of transportation equipment, infrastructure, operations management, and minimize transportation costs. The methods used include data collection, data processing, and the application of mathematical models to determine the optimal route with iteration methods such as the Simplex Method or Simplex Algorithm (SIMPLEKS), Modified Distribution Method (MODI), Vogel's Approximation Method (VAM), North-West Corner Method, Least Cost Method, and Initial Cost Minimum Method (ICMM). This study successfully shows that this method is able to reduce the cost of reducing carbon emissions, significantly reduce shipping costs and increase the efficiency of goods distribution that can be applied to complex distribution systems, support efficiency, and sustainability of transportation management. Using Linear programming and transportation methods to reduce SME costs and produce more efficient costs and fast solutions. In general,optimizationThis supports economic development, efficiency and sustainability of transportation management.
Application of Genetic Algorithm on Knapsack Problem for Optimization of Goods Selection Indah Mauludina Hasanah; Lukman Widoyo Mulyo; Muhammad Fardeen Khan; Rizki Apriva Hidayana
International Journal of Quantitative Research and Modeling Vol. 6 No. 2 (2025): International Journal of Quantitative Research and Modeling
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v6i2.1020

Abstract

Knapsack Problemis one of the combinatorial optimization problems that often arise in everyday life, especially in making decisions about selecting goods with limited capacity. This study combines two previous studies that apply genetic algorithms to real cases: the selection of basic necessities and packaged fruits in limited containers. Genetic algorithms are used because they are flexible and able to find more than one optimal solution. The process includes the formation of an initial population, fitness evaluation, selection (roulette wheel), crossover, and mutation. From the two case studies analyzed, it was found that genetic algorithms consistently produce increased fitness between generations and are able to maximize the value of goods without exceeding capacity or budget limits. This study strengthens the potential of genetic algorithms as an effective method in solving Knapsack Problems based on real needs.
Determination of Collective Premiums for Seven Benefits of BPJS Employment Insurance JKK Program Using Poisson-Normal Aggregate Distribution Nazla Aqira Maghfirani; Rizki Apriva Hidayana
International Journal of Business, Economics, and Social Development Vol. 6 No. 1 (2025): International Journal of Business, Economics, and Social Development (IJBESD)
Publisher : Rescollacom (Research Collaborations Community)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijbesd.v6i1.877

Abstract

Work Accident Insurance (JKK) is one of the programs of the Social Security Administering Agency (BPJS) for Employment. Insurance brokers need to make an initial estimate of the premium to determine the collective premium for JKK. Premium calculations can be done using the aggregate distribution method. The total loss of the insurance policy can be owned by the random variable of the aggregate distribution. In calculating the premium using the aggregate distribution, one of the principles that can be used is the standard deviation principle. Based on this principle, the amount of the premium can be calculated by the standard deviation of the aggregate distribution. This study uses the aggregate Poisson-Normal distribution to calculate the collective premium based on the seven benefits of the JKK BPJS Ketenagakerjaan Bojongsoang program. The data used are the number of claim events and the number of claims from the seven benefit claims of JKK BPJS Ketenagakerjaan Bojongsoang participants for the 2022 period. The principle used in calculating the collective premium with the aggregate distribution is the standard deviation principle. The results of the analysis show that the Poisson distribution is followed by claim frequency data and the Normal distribution is followed by the amount of the claim. This study shows that the amount of collective premium calculated tends to be greater than the amount of collective premium sourced from existing data of BPJS Ketenagakerjaan Bojongsoang company. It is expected for insurance brokers and insurance companies to consider this study.
Analysis of Economic Growth and Tourism Potential in Tanjung Lesung, Panimbang, Banten as a Creative Economy Destination Rizki Apriva Hidayana; Mugi Lestari
International Journal of Business, Economics, and Social Development Vol. 6 No. 1 (2025): International Journal of Business, Economics, and Social Development (IJBESD)
Publisher : Rescollacom (Research Collaborations Community)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijbesd.v6i1.879

Abstract

Tanjung Lesung, located in Pandeglang Regency, Banten, has been designated as a Special Economic Zone (SEZ) for Tourism with the aim of encouraging regional economic growth and improving community welfare. This study analyzes the impact of SEZ on the local economy using qualitative and quantitative approaches. Data were obtained through in-depth interviews, surveys, field observations, and documentation studies. The results of the study indicate that the Tanjung Lesung SEZ has contributed positively to increasing community income by 52% and reducing the unemployment rate by 33%. In addition, investment in the tourism sector encourages business growth in the hospitality, culinary, and tourism services sectors. However, the development of SEZ also faces several challenges, such as limited infrastructure, readiness of local workers, and social and environmental impacts. Limited infrastructure, especially transportation access, is an obstacle in supporting the growth of the tourism sector. In addition, many local workers do not yet have the skills needed by the tourism industry. Environmental impacts, such as increasing waste volume and conversion of agricultural land, are also major concerns. Therefore, a comprehensive strategy is needed through improving infrastructure, strengthening human resource capacity, and implementing sustainable environmental management policies. With the right steps, Tanjung Lesung Special Economic Zone can become a successful model for inclusive and sustainable tourism-based economic development in Indonesia.
Application of Mathematical Concepts in the Health Sector through Data Analysis Learning Using Microsoft Excel for Senior High School Students at SMA Pasundan Majalaya Abdul Gazir Syarifudin; Rizki Apriva Hidayana; Rika Amelia; Tubagus Robby Megantara; Nenden Siti Nur Kholipah; Athaya Zahrani Irmansyah; Indah Mauludina Hasanah; Wulan Anggraeni; Ida Widiawati; Wiwin Widayani; Desi Hidayati; Anita Megawati Fajrin
International Journal of Research in Community Services Vol. 7 No. 1 (2026): International Journal of Research in Community Service (IJRCS)
Publisher : Research Collaboration Community (Rescollacom)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijrcs.v7i1.1165

Abstract

This community service program aims to strengthen students’ numeracy, digital literacy, and health literacy through the application of mathematical concepts in health data analysis using Microsoft Excel. The activity was conducted at SMA Pasundan Majalaya and involved senior high school students as participants. The program was designed in the form of socialization and hands-on training sessions, including basic arithmetic operations, simple data analysis, logical functions, data visualization techniques, and simple regression analysis applied to health-related data. The implementation employed a participatory learning approach to support students’ understanding and engagement in the learning process. The results indicate an improvement in students’ ability to process, analyze, and interpret health data using Microsoft Excel. This program demonstrates that contextual and application-based mathematics learning can effectively enhance students’ analytical skills and awareness of the role of mathematics in real-world health contexts.
Co-Authors Angellyca Leoni Manuela Anita Megawati Fajrin Athaya Zahrani Irmansyah Desi Hidayati Ida Widiawati, Ida Indah Mauludina Hasanah Indah Mauludina Hasanah Lukman Widoyo Mulyo Moch Panji Agung Saputra Mugi Lestari Muhammad Fardeen Khan Nazla Aqira Maghfirani Nenden Siti Nur Kholipah Nestia Lianingsih Nicko Meizani Reivani Putri Berlinda Harahap Rika Amelia Tina Yoefitri Tubagus Robby Megantara Widayani, Wiwin Wulan Anggraeni