Revolusi Digital di Kebun Mint: Pemetaan Bibliometrik Perkembangan Sistem Sensor IoT untuk Smart Farming Digital Revolution in Mint Cultivation: A Bibliometric Mapping of IoT-Based Sensor Systems for Smart Farming

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Razaqi

Widiatmoko

Universitas Merdeka Madiun

Widiatmoko

Universitas Merdeka Madiun

Nurwantara

Universitas Merdeka Madiun

Budi

Universitas Merdeka Madiun

Abstract

Integrasi teknologi Internet of Things (IoT) dan sensor semakin mendorong perkembangan sistem pertanian cerdas, termasuk dalam budidaya tanaman mint yang memiliki nilai ekonomi tinggi. Meski demikian, penelitian mengenai penerapan IoT pada tanaman mint masih terbatas dan tersebar di berbagai disiplin ilmu. Penelitian ini bertujuan memetakan perkembangan riset terkait aplikasi IoT dan sensor pada smart farming tanaman mint melalui pendekatan bibliometrik. Data dikumpulkan dari Scopus untuk periode 1974–2025, menghasilkan 124 dokumen awal yang kemudian diseleksi menjadi 64 publikasi relevan. Analisis menggunakan Biblioshiny mencakup tren publikasi, performa sitasi, jejaring kolaborasi, dan struktur konseptual. Hasil penelitian menunjukkan bahwa topik ini berkembang secara multidisipliner dengan kontribusi utama dari bidang teknik, agronomi, dan kecerdasan buatan. Jurnal inti seperti Smart Agricultural Technology dan Nano-Micro Letters mendominasi publikasi. Kata kunci dominan menegaskan peran IoT, precision agriculture, dan deep learning sebagai tema sentral. Studi ini memberikan gambaran ringkas tren penelitian serta peluang pengembangan di masa depan.

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Alazab, M., Tang, M., & Al-Hawawreh, M. (2021). “Deep Learning for Cybersecurity and IoT: Challenges and Future Directions.” Computers & Security, 108, 102393.

Aria, M., & Cuccurullo, C. (2017). "bibliometrix: An R-tool for Comprehensive Science Mapping Analysis." Journal of Informetrics, 11(4), 959–975.

Atlam, H. F., Walters, R. J., & Wills, G. B. (2020). “Fog Computing and the Internet of Things: A Review.” Future Generation Computer Systems, 108, 109–125.

Jeon, S., et al. (2022). “Integration of AI and sensor networks for environmental and industrial monitoring.” Journal of Cleaner Production, 354, 131693.

Khan, A., et al. (2018). “UAVs and IoT for agriculture applications.” Computers and Electronics in Agriculture, 153, 69–78.

Khan, M. A., & Salah, K. (2018). "IoT Security: Review, Blockchain Solutions, and Open Challenges." Future Generation Computer Systems, 82, 395–411.

Kim, J., Park, D., & Lee, S. (2023). Cloud-integrated IoT frameworks for real-time agricultural monitoring. Sensors and Systems.

Chen, L., Wang, Q., & Luo, T. (2023). IoT-based environmental sensing systems for sustainable agriculture. Journal of Smart Farming Technology.

Chen, Y., et al. (2019). “Recent developments in data-driven sensing and detection technologies.” Sensors and Actuators B: Chemical, 282, 952–965.

Colomina, I., & Molina, P. (2014). “Unmanned aerial systems for photogrammetry and remote sensing: A review.” ISPRS Journal of Photogrammetry and Remote Sensing, 92, 79–97.

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.

Dwivedi, Y. K., Hughes, L., Ismagilova, E., et al. (2021). “Artificial Intelligence, Machine Learning, and Big Data in Emerging Research Domains: A Bibliometric Review.” International Journal of Information Management, 57, 102381

El-Barbri, N., et al. (2020). “Intelligent classification systems and sensor technologies: Advances and applications.” Sensors, 20(14), 3890.

Harzing, A.-W., & Alakangas, S. (2016). "Google Scholar, Scopus and the Web of Science: A longitudinal and cross-disciplinary comparison." Scientometrics, 106(2), 787–804.

Heinke, L., et al. (2019). “Functional sensor materials and emerging sensing technologies.” Advanced Materials, 31(26), 1808253.

Kim, Y., et al. (2020). “IoT-based sensing systems for aroma and gas detection: Recent advances and applications.” IEEE Internet of Things Journal, 7(6), 5053–5065.

Li, X., & Huang, Y. (2020). Trends in smart farming research: A bibliometric analysis. Agricultural Informatics Journal.

Maes, W. H., & Steppe, K. (2019). “Perspectives for remote sensing with unmanned aerial vehicles in precision agriculture.” Trends in Plant Science, 24(2), 152–164.

Martinez, R., & Lopez, G. (2021). Global collaboration trends in IoT agriculture research. International Journal of Agricultural Technology.

Martínez-García, M., Sánchez-Romero, J. L., Toledo-Moreo, J., & Bernal-Crespo, V. (2021). "A Bibliometric Analysis of Machine Learning Applications in Healthcare." Applied Sciences, 11(9), 4113.

Moed, H. F. (2005). Citation Analysis in Research Evaluation. Springer.

Newman, M. E. J. (2005). “Power Laws, Pareto Distributions and Zipf’s Law.” Contemporary Physics, 46(5), 323–351.

Ochoa, M., & Rivera, J. (2021). Bibliometric mapping of IoT applications in precision farming. Scientometrics Review.

Pao, M. L. (1985). “Lotka’s Law: A Theoretical and Empirical Review.” Journal of the American Society for Information Science, 37(1), 26–33.

Qiu, S., et al. (2019). “Quantitative analysis of volatile organic compounds using sensor arrays and machine learning.” ACS Sensors, 4(10), 2763–2770.

Rahman, A., Putra, M., & Siregar, B. (2022). Soil moisture IoT sensors for irrigation optimization. Indonesian Journal of Agricultural Engineering.

Rasekh, M., et al. (2020). “Metal oxide gas sensors and their application in electronic nose systems.” Journal of Materials Chemistry C, 8(48), 17148–17173.

Rousseau, R., & Rousseau, S. (2000). “Lotka: A Program to Fit a Power Law Distribution to Observed Frequency Data.” Cybermetrics, 4(1).

Saidi, T., et al. (2018). “A hybrid electronic nose for mint essential oil classification using chemometric methods.” Sensors and Actuators B: Chemical, 259, 31–39.

Silva, F., & Duarte, P. (2021). Environmental monitoring for mint cultivation using IoT sensors. Journal of Herb Technology.

Singh, P., et al. (2021). “Characterization of Mentha species and essential oils using electronic nose and chemometric analysis.” Industrial Crops and Products, 170, 113735.

Singh, R., Patel, N., & Kumar, S. (2022). IoT-based herbal crop monitoring systems: A review. Herbal Production Science

Thelwall, M., & Sud, P. (2016). “Bibliometrics for Academic Evaluation: Articles, Book Chapters, and the Excel h-index.” Journal of Informetrics, 10(2), 336–345.

Torresan, C., et al. (2017). “Forestry applications of UAVs in Europe: A review.” International Journal of Remote Sensing, 38(8–10), 2427–2447.

Wen, T., et al. (2021). “Characterization of Mentha species using electronic nose and chemometric analysis.” Industrial Crops and Products, 170, 113735.

Wilson, A. D. (2016). “Electronic-nose technologies and advancements in machine olfaction.” Sensors, 16(11), 1898.

Yang, Y., & Zhang, Z. (2021). “Machine learning–assisted sensing systems: A comprehensive review.” IEEE Sensors Journal, 21(18), 20345–20360.

Zhang, C., & Kovacs, J. M. (2012). “The application of small UAVs for precision agriculture: a review.” Precision Agriculture, 13(6), 693–712.

Zhang, W., & Yao, T. (2020). Advances in sensor technologies for precision agriculture. Precision Agriculture Systems.

Zupic, I., & Cater, T. (2015). "Bibliometric Methods in Management and Organization." Organizational Research Methods, 18(3), 429–472.

Widiatmoko, Universitas Merdeka Madiun

Program Studi Agroteknologi, Fakultas Pertanian, Universitas Merdeka Madiun Jl. Serayu No.79, Kota Madiun, Jawa Timur 63133

Widiatmoko, Universitas Merdeka Madiun

Program Studi Agroteknologi, Fakultas Pertanian, Universitas Merdeka Madiun, Jl. Serayu No.79, Madiun

Nurwantara, Universitas Merdeka Madiun

Program Studi Agroteknologi, Fakultas Pertanian, Universitas Merdeka Madiun, Jl. Serayu No.79, Madiun

Budi, Universitas Merdeka Madiun

Program Studi Agroteknologi, Fakultas Pertanian, Universitas Merdeka Madiun, Jl. Serayu No.79, Madiun
Title Revolusi Digital di Kebun Mint: Pemetaan Bibliometrik Perkembangan Sistem Sensor IoT untuk Smart Farming
Issue: Vol. 26 No. 2 (2025): JURNAL AGRI-TEK
Section Articles
Published: Sep 30, 2025
DOI: https://doi.org/10.33319/agtek.v26i2.197
Keywords: bibliometric, IoT, mint, pertanian presisi, sensor, smart farming
Author
  • Razaqi
  • Widiatmoko
    Universitas Merdeka Madiun
    Program Studi Agroteknologi, Fakultas Pertanian, Universitas Merdeka Madiun Jl. Serayu No.79, Kota Madiun, Jawa Timur 63133
  • Widiatmoko
    Universitas Merdeka Madiun
    Program Studi Agroteknologi, Fakultas Pertanian, Universitas Merdeka Madiun, Jl. Serayu No.79, Madiun
  • Nurwantara
    Universitas Merdeka Madiun
    Program Studi Agroteknologi, Fakultas Pertanian, Universitas Merdeka Madiun, Jl. Serayu No.79, Madiun
  • Budi
    Universitas Merdeka Madiun
    Program Studi Agroteknologi, Fakultas Pertanian, Universitas Merdeka Madiun, Jl. Serayu No.79, Madiun
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How to Cite
Razaqi, A. F. ., Widiatmoko, M. L. ., Widiatmoko, M. L. ., Nurwantara, M. P. ., & Budi, L. S. . (2025). Revolusi Digital di Kebun Mint: Pemetaan Bibliometrik Perkembangan Sistem Sensor IoT untuk Smart Farming: Digital Revolution in Mint Cultivation: A Bibliometric Mapping of IoT-Based Sensor Systems for Smart Farming. JURNAL AGRI-TEK : Jurnal Penelitian Ilmu-Ilmu Eksakta, 26(2), 53–72. https://doi.org/10.33319/agtek.v26i2.197
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