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All Journal Mandalika Mathematics and Educations Journal Griya Journal of Mathematics Education and Application
Zahra, Khoiruz
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Education Mathematics

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Tren, Inovasi, dan Keberlanjutan dalam Mathematical Modelling untuk Food Science: Analisis Bibliometrik 2014–2024 Afriansyah, Dilla; Perdhana, Firman Fajar; Zahra, Khoiruz; Adriani, Ika Reskiana
Mandalika Mathematics and Educations Journal Vol 6 No 2 (2024): Edisi Desember
Publisher : FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jm.v6i2.8078

Abstract

Mathematical Modelling is an essential tool in various aspects of Food Science, particularly in addressing complex challenges such as production process optimization, shelf-life prediction, food waste management, and food safety assurance. This article aims to provide an in-depth analysis of research trends in Mathematical Modelling within Food Science during the 2014–2024 period, based on 350 documents indexed in Scopus. A bibliometric approach was employed using VOSviewer to map keyword relations, collaboration patterns among researchers, and geographical distribution of studies. The results revealed four main clusters of research topics: food safety and disease (Blue Cluster), sustainability and environmental issues (Red Cluster), prediction and process optimization (Yellow Cluster), and technology and innovation in food processing (Green Cluster). These findings underline the critical role of Mathematical Modelling in tackling global food challenges. This article provides recommendations to expand international collaborations and explore artificial intelligence integration in Mathematical Modelling research for food in the future. Keywords: Bibliometrix, Food Science, Mathematical Modelling
The Agricultural Insurance: Explore Trends and Advances Over the Last Two Decades ADRIANI, IKA RESKIANA; Ekasasmita, Wahyuni; Afriansyah, Dilla; Zahra, Khoiruz
Mandalika Mathematics and Educations Journal Vol 7 No 2 (2025): Edisi Juni
Publisher : FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/jm.v7i2.9018

Abstract

The agricultural sector faces major risks due to extreme climate change, market uncertainty and economic fluctuations, which can destabilize global food production. Agricultural insurance, despite its importance as a risk mitigation tool for farmers, still has limited article reviews compared to other insurance sectors such as health, life, and property. This study aims to conduct a bibliometric analysis of global research on agricultural insurance over the past two decades, focusing on publication trends, the most influential countries and journals, keyword analysis, and providing directions for future research. The study used data from Scopus with a total of 643 documents. Analysis was conducted using VOS viewer, RStudio, and Tableau to visualize collaboration patterns, dominant keywords, and global publication trends. The analysis shows a significant increase in the number of studies on agricultural insurance, which reinforces the urgency of insurance in supporting global food stability. The implications of this research point to the need to develop insurance models that are technology-based and more adaptive to climate change, especially to expand access for smallholder farmers in developing countries. Recommendations for future research are to strengthen cross-sector collaboration and technological innovation to support the sustainability and resilience of the agricultural sector in the future.
Matematika dalam Penelitian Kopi: Visualisasi Jaringan dan Klasterisasi Topik Berdasarkan Data Scopus Afriansyah, Dilla; Fajar Perdhana, Firman; Zahra, Khoiruz; Reskiana Adriani, Ika
Griya Journal of Mathematics Education and Application Vol. 5 No. 2 (2025): Juni 2025
Publisher : Pendidikan Matematika FKIP Universitas Mataram

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29303/griya.v5i2.657

Abstract

This study aims to explore the scientific landscape of mathematical applications in coffee-related research using a bibliometric approach. By analyzing 99 documents retrieved from the Scopus database, this study identifies global research trends, productive authors and institutions, country-level contributions, and dominant subject areas. The analysis includes publication patterns, keyword co-occurrence networks, and author collaboration clusters visualized using VOSviewer. The findings show a significant rise in scientific interest since 2016, with the United States and Indonesia leading in publication volume. Although the research spans multiple disciplines such as mathematics, engineering, agriculture, and computer science, collaboration among researchers remains limited, with many author clusters operating independently. The keyword clustering reveals six major themes ranging from bioinformatics and plant disease modeling to chemical composition and teaching philosophy. These findings underscore the growing role of mathematical methods in coffee research and highlight the need for stronger interdisciplinary and international collaboration to support innovation in coffee science and production.
Co-Authors Adriani, Ika Reskiana Dilla Afriansyah Firman Fajar Perdhana Wahyuni Ekasasmita