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All Journal CAUCHY: Jurnal Matematika Murni dan Aplikasi Jurnal Ilmu-Ilmu Peternakan (Indonesian Journal of Animal Science) Al-Jabar : Jurnal Pendidikan Matematika Jurnal Ilmiah Peuradeun Jurnal Ilmiah Didaktika : Media Ilmiah Pendidikan dan Pengajaran Desimal: Jurnal Matematika BAREKENG: Jurnal Ilmu Matematika dan Terapan JTAM (Jurnal Teori dan Aplikasi Matematika) Jurnal Soshum Insentif Jurnal Matematika UNAND Jurnal Statistika dan Matematika (Statmat) Islamic Journal of Integrated Science Education International Journal of Applied Mathematics, Sciences, and Technology for National Defense Transcendent Journal of Mathematics and Applications Limits: Journal of Mathematics and Its Applications
Vina Apriliani
Universitas Islam Negeri Ar-Raniry Banda Aceh
Religion Arts Humanities Biochemistry, Genetics & Molecular Biology Chemistry Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Energy Engineering Environmental Science Law, Crime, Criminology & Criminal Justice Mathematics Mechanical Engineering Physics Social Sciences Transportation Other

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Optimal Bonus-Malus Premium with the Claim Frequency Distribution is Negative Binomial and the Claim Severity Distribution is Truncated Weibull Maulidi, Ikhsan; MAULIDIA, IZZAH; Radhiah, Radhiah; Apriliani, Vina
Jurnal Matematika UNAND Vol. 15 No. 2 (2026)
Publisher : Departemen Matematika dan Sains Data FMIPA Universitas Andalas Padang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/jmua.15.2.179-195.2026

Abstract

The optimal bonus-malus system is a system for determining the amount of premium in the next period based on the frequency and severity of claims filed by policyholders in the previous period. In this article, we study the insurance premium formula using the optimal bonus-malus system with the claim frequency has a negative binomial distribution and the claim severity has a truncated Weibull distribution. The method to derive the bonus-malus formula uses a Bayes solution with a quadratic loss function. The formula obtained has been also applied to the data of motor vehicle insurance to calculate the risk premium that must be paid by the policyholder. From the calculation results, the insurance premiums that use the optimal bonus-malus system with a truncated Weibull distribution are more profitable for both the company and the insurer than the Weibull distribution.
Integration of Qur'anic Values in Mathematics Learning: A Bibliometric Analysis Lestari, Fitria; Farid, Fajri; Syazali, Muhamad; Putra, Fredi Ganda; Maulidi, Ikhsan; Apriliani, Vina
Islamic Journal of Integrated Science Education (IJISE) Vol. 4 No. 2 (2025): July
Publisher : Program Studi Tadris IPA, Fakultas Tarbiyah dan Ilmu Keguruan, Universitas Islam Negeri (UIN) Syekh Wasil Kediri

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30762/ijise.v4i2.5921

Abstract

The integration of Qur'anic values in learning is an increasingly popular field in Education, therefore this research aims to determine the integration of Qur'anic values in Mathematics Learning This research uses a descriptive qualitative method through literature study research techniques. The data obtained based on 12 journal articles analyzed is based on a critical analysis of the available literature (articles based on scientific novelty content from 2017 to 2024 indexed on Google Scholar) data analysis techniques using VOS viewer software version 1.6.16 for graphical bibliometric mapping. Based on the data obtained Research shows the importance of combining Islamic values with mathematics to build character and advance education. Various models are proposed to integrate mathematical concepts from the Quran, such as numbers, relationships, operations, and measurements, in learning. This integration not only improves students' understanding of mathematics, but also creates a well-rounded educational experience. Therefore, it is highly recommended for teachers to teach mathematics by integrating with the values or verses of the Quran. So that students feel that learning mathematics useful for the development of student competencies.
Average-based fuzzy time series for forecasting blood bag availability: Implications for health resilience and emergency preparedness in Banda Aceh, Indonesia Ikhsan Maulidi; Nurafni Fazriani; Radhiah Radhiah; Vina Apriliani; Sarbaini
International Journal of Applied Mathematics, Sciences, and Technology for National Defense Vol. 4 No. 1 (2026): International Journal of Applied Mathematics, Sciences, and Technology for Nati
Publisher : FoundAE

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58524/app.sci.def.v4i1.1138

Abstract

Background: Blood availability remains a major challenge in healthcare systems, particularly in developing countries where the demand for blood often exceeds the available supply. Accurate forecasting of blood collection is therefore important to support effective blood inventory management at blood transfusion units. Aims: This study aims to apply the Average-Based Fuzzy Time Series method to forecast the number of collected blood bags at the Blood Transfusion Unit (UTD) of the Indonesian Red Cross in Banda Aceh, both in total and by blood type. Method: Monthly blood collection data from January 2016 to September 2020 were analyzed using the Average-Based Fuzzy Time Series model. The forecasting procedure involved constructing fuzzy intervals using the average-based approach, forming fuzzy logical relationships, and performing defuzzification. Model performance was evaluated using Mean Squared Error (MSE) and Average Forecasting Error Rate (AFER). Result: The second-order model provided the best forecasting performance with an AFER value of 13.67% and an accuracy of approximately 86.33%, producing a prediction of 2054 blood bags for October 2020. Forecasting by blood type yielded predictions of 529 (A), 702 (O), 738 (B), and 154 (AB) blood bags. Conclusion: The results indicate that the Average-Based Fuzzy Time Series method is effective for forecasting blood bag availability and can support planning and management of blood supply at blood transfusion units. Furthermore, the proposed approach has potential applications in defense and emergency contexts by supporting medical logistics planning, improving preparedness, and enhancing the resilience of blood supply systems during military operations and disaster response.
Co-Authors Alim Misbullah Alim Misbullah Alindo, Sesda Budi Azhari Chintya Hayati Fahrul Razi Fanny Novika Farid, Fajri Febriana, Diana Fitria Lestari Fredi Ganda Putra Hafnani Hafnani Herlina Herlina Ikhsan Maulidi Ikhsan Maulidi Ikhsan Maulidi Ikhsan Maulidi Ikhsan Maulidi Johan Yunus Johan Yunus Juanda Kelana Putra M. Faisi Ikhwali Mahmudi Mahmudi Mahyus Ihsan Maulidi, Ikhsan MAULIDIA, IZZAH Muhamad Syazali Muhammad Abrar Muliawan, Nadia Fitri Mulyeni, Sri Nova Novita, Windi Nur Oktaviana, Shaqia Nurafni Fazriani Nuralam Syamsuddin Nurmaulidar Nurmaulidar Radhiah Radhiah Radhiah Radhiah Radhiah, Radhiah Rini Oktavia Rini Oktavia Rofiqul Umam Sarbaini Siti Rusdiana Suardi Nur Syazali, Muhammad Uswah Uswah Uswah Valentika, Nina Werry Febrianti Wibowo, Bonno Andri Yunus, Johan Zahnur, Zahnur Zairisma Zairisma Zairisma, Zairisma