MEMETAKAN MASA DEPAN PERTANIAN: ANALISIS BIBLIOMETRIK MULTIDIMENSI TERHADAP PERKEMBANGAN PERTANIAN, PEMBANGUNAN BERKELANJUTAN, DAN SAINS PERTANIAN

Authors

  • Rifki Muhamad Imadudin Siliwangi University image/svg+xml Author
  • Wilva Ramadayanti Siliwangi University image/svg+xml Author
  • Irpan Nudin Universitas Riyadlul Ulum, Indonesia Author

Keywords:

bibliometrik, pertanian berkelanjutan, pembangunan pertanian, ketahanan pangan, perubahan iklim

Abstract

Penelitian ini menyajikan analisis bibliometrik multidimensi terhadap literatur ilmiah yang berkaitan dengan pembangunan pertanian, keberlanjutan, dan sains pertanian menggunakan data dari basis data Scopus. Dengan memanfaatkan VOSviewer, pemetaan jaringan kata kunci dilakukan untuk mengidentifikasi struktur intelektual, klaster tematik, dan tren penelitian yang berkembang dalam periode 2023-2025. Hasil analisis menunjukkan bahwa jaringan penelitian terbagi ke dalam tiga klaster utama: (1) Klaster Biru yang berfokus pada kebijakan, ekonomi, dan pembangunan berkelanjutan; (2) Klaster Hijau yang berorientasi pada teknologi pertanian cerdas, perubahan iklim, dan manajemen sumber daya; serta (3) Klaster Merah yang mewakili fondasi sains dasar meliputi agrokimia dan biologi tanah. Analisis overlay temporal mengungkapkan bahwa topik-topik seperti microbiology, carbon emission, dan agricultural economics merupakan tren penelitian termutakhir (2024,3+), sementara machine learning dan remote sensing telah mengalami pengarusutamaan. Peta kepadatan mengonfirmasi bahwa agricultural development dalam konteks Tiongkok mendominasi wacana global. Temuan ini berimplikasi pada pentingnya integrasi lintas disiplin antara sains dasar, inovasi teknologi, dan kerangka kebijakan untuk mewujudkan ketahanan pangan yang berkelanjutan di tengah tekanan perubahan iklim.

 

References

Aria, M., & Cuccurullo, C. (2017). Bibliometrix: An R-tool for comprehensive science mapping analysis. Journal of Informetrics, 11(4), 959–975.

Balogh, P., Konár, Z., Gabnai, Z., Pál, G., Bai, A., & Papp, S. (2020). Research trends in agricultural sustainability: A systematic bibliometric analysis. Sustainability, 12(20), 8503.

Bhattacharyya, P. N., Goswami, M. P., & Bhattacharyya, L. H. (2020). Perspective of beneficial microbes in agriculture under the changing climatic scenario: A review. Journal of Phytology, 12, 26–41.

Bornmann, L., & Mutz, R. (2015). Growth rates of modern science: A bibliometric analysis based on the number of publications and cited references. Journal of the Association for Information Science and Technology, 66(11), 2215–2222.

Chen, X., Zhang, Y., & Liu, W. (2024). Mapping the intellectual landscape of China's agricultural development research: A bibliometric analysis. Agricultural Systems, 218, 103684.

Donthu, N., Kumar, S., Mukherjee, D., Pandey, N., & Lim, W. M. (2021). How to conduct a bibliometric analysis: An overview and guidelines. Journal of Business Research, 133, 285–296.

Elsevier. (2024). Research trends in sustainable agriculture and food security: A Scopus analysis. Elsevier Research Intelligence Report. https://www.elsevier.com/research-intelligence

FAO. (2023). The future of food and agriculture: Drivers and triggers for transformation. Food and Agriculture Organization of the United Nations. https://www.fao.org/publications/home/fao-flagship-publications/the-future-of-food-and-agriculture/en

FAO. (2024). The state of food and agriculture 2024: Financing to end hunger and malnutrition for the transformation of food systems. Food and Agriculture Organization of the United Nations. https://www.fao.org/publications/home/fao-flagship-publications/the-state-of-food-and-agriculture/en

Farooque, A. A., Zaman, Q. U., Groulx, D., & Schumann, A. W. (2022). Precision agriculture for sustainable crop production: A bibliometric review of current status and future prospects. Agronomy, 12(3), 694.

Gluckman, P. D., Bardsley, A., & Kaiser, M. (2021). Brokerage at the science–policy interface: From conceptual framework to practical guidance. Humanities and Social Sciences Communications, 8, 84.

Goap, A., Sharma, D., Shukla, A. K., & Rama Krishna, C. (2018). An IoT based smart irrigation management system using Machine Learning and open source technologies. Computers and Electronics in Agriculture, 155, 41–49.

IPBES. (2024). Assessment report on the interlinkages among biodiversity, water, food and health. Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services.

IPCC. (2022). Climate Change 2022: Impacts, adaptation and vulnerability. Contribution of Working Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press.

Liakos, K. G., Busato, P., Moshou, D., Pearson, S., & Bochtis, D. (2018). Machine learning in agriculture: A review. Sensors, 18(8), 2674.

Liu, J., Tao, F., & Zhang, Z. (2023). Remote sensing-based monitoring of crop growth and agricultural land use in China: A review of recent advances. Remote Sensing of Environment, 287, 113465.

Machado, C. G., Winroth, M. P., & Ribeiro da Silva, E. H. D. (2020). Sustainable manufacturing in Industry 4.0: An emerging research agenda. International Journal of Production Research, 58(5), 1462–1484.

Moral-Muñoz, J. A., Herrera-Viedma, E., Santisteban-Espejo, A., & Cobo, M. J. (2020). Software tools for conducting bibliometric analysis in science: An up-to-date review. Profesional de la Información, 29(1), e290103.

Popp, J., Pető, K., & Nagy, J. (2017). Pesticide productivity and food security: A review. Agronomy for Sustainable Development, 33(1), 243–255.

Sarkar, S., Pramanik, M., Panda, S., & Dey, S. K. (2023). Application of machine learning in smart agriculture: Recent trends and future prospects. Journal of Cleaner Production, 421, 138457. https://doi.org/10.1016/j.jclepro.2023.138457

Sugiyono, M. E., & Widiyanto, B. (2023). Pemetaan agenda riset pertanian Indonesia berbasis analisis bibliometrik Scopus 2018–2022: Implikasi terhadap kebijakan riset nasional. Jurnal Kebijakan Pertanian, 17(2), 115–134.

Van Eck, N. J., & Waltman, L. (2010). Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics, 84(2), 523–538.

Van Eck, N. J., & Waltman, L. (2023). VOSviewer manual (Version 1.6.20). Leiden University.

Weiss, M., Jacob, F., & Duveiller, G. (2020). Remote sensing for agricultural applications: A meta-review. Remote Sensing of Environment, 236, 111402.

Woolf, D., Solomon, D., & Lehmann, J. (2021). Land restoration in food security programmes: Synergies with climate change mitigation. Climate Policy, 21(Suppl. 1), 40–55.

Zupic, I., & Čater, T. (2015). Bibliometric methods in management and organization. Organizational Research Methods, 18(3), 429–472.

Published

2026-05-31

How to Cite

Rifki Muhamad Imadudin, Wilva Ramadayanti, & Irpan Nudin. (2026). MEMETAKAN MASA DEPAN PERTANIAN: ANALISIS BIBLIOMETRIK MULTIDIMENSI TERHADAP PERKEMBANGAN PERTANIAN, PEMBANGUNAN BERKELANJUTAN, DAN SAINS PERTANIAN. An-Nabaat: Journal of Plant Science and Agrotechnology, 1(1), 1-11. https://an-nabaat.uniru.ac.id/an-nabaat/article/view/1