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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
Hasanah, Indah Mauludina
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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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Application of Genetic Algorithm on Knapsack Problem for Optimization of Goods Selection Hasanah, Indah Mauludina; Mulyo, Lukman Widoyo; Khan, Muhammad Fardeen; Hidayana, Rizki Apriva
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.v6i2.1020

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.
Application of Genetic Algorithm on Knapsack Problem for Optimization of Goods Selection Hasanah, Indah Mauludina; Mulyo, Lukman Widoyo; Khan, Muhammad Fardeen; Hidayana, Rizki Apriva
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.v6i2.1020

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.
Analyzing Public Perception on Integrating Ride-Hailing with Emergency Health Services Megantara, Tubagus Robbi; Hidayana, Rizki Apriva; Hasanah, Indah Mauludina
International Journal of Business, Economics, and Social Development Vol. 7 No. 1 (2026): 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.v7i1.1086

Abstract

Traditional Emergency Health Services (EHS) face numerous challenges, including response time efficiency. The integration of ride-hailing platforms offers an innovative solution, yet public perception of this concept remains underexplored. This study investigates public perception through a quantitative survey of 100 respondents, analyzed as a whole and as two subgroups: those with prior EHS experience (n=48) and those without (n=52). The results reveal exceptionally strong and broad public support for this integration. A key finding is a significant "experience gap": respondents with prior EHS experience demonstrate confident demand with less hesitation, while non-users show more theoretical support with higher neutrality, particularly regarding personal adoption. Despite this difference, both groups show a high consensus on fundamental requirements such as patient safety, driver competency, and the availability of medical equipment. This study concludes that there is high social viability for integrating ride-hailing and EHS. The findings provide a clear mandate for stakeholders to proceed with innovation, on the condition that system development prioritizes the safety and reliability standards expected by the public. This research lays the groundwork for the next stage: the development of mathematical models for a decision-support system to translate this concept into an effective and trustworthy solution. Keywords: ride-hailing, emergency health services, public perception, mathematical modeling, decision-support systems.
Application of Mathematical Concepts in the Health Sector through Data Analysis Learning Using Microsoft Excel for Senior High School Students at SMA Pasundan Majalaya Syarifudin, Abdul Gazir; Hidayana, Rizki Apriva; Amelia, Rika; Megantara, Tubagus Robby; Kholipah, Nenden Siti Nur; Irmansyah, Athaya Zahrani; Hasanah, Indah Mauludina; Anggraeni, Wulan; Widiawati, Ida; Widayani, Wiwin; Hidayati, Desi; Fajrin, Anita Megawati
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 Amelia, Rika Fajrin, Anita Megawati Hidayana, Rizki Apriva Hidayati, Desi Ida Widiawati, Ida Irmansyah, Athaya Zahrani Khan, Muhammad Fardeen Kholipah, Nenden Siti Nur Megantara, Tubagus Robbi Megantara, Tubagus Robby Mulyo, Lukman Widoyo Widayani, Wiwin Wulan Anggraeni, Wulan