Implementasi Big Data dalam Manajemen Data Bidang Pertanian

Marza Dona, Jhon Veri

Sari


Big data belum cukup populer dimanfaatkan dalam bidang pertanian. Penelitian bertujuan untuk mengkaji pemanfaatan big data dalam manajemen data pertanian. Penelitian ini ditulis menggunakan metode Systematic Literature Review (SLR) yang bermanfaat untuk mengidentifikasi, mengevaluasi, dan menyimpulkan hasil penelitian terkait topik yang dikaji secara sistematis dan terstruktur. Dalam pelaksanaannya, penelitian ini menggunakan model PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses), yang bertujuan untuk memastikan transparansi, dan akuntabilitas dalam setiap tahapan proses SLR. Aplikasi yang digunakan pada penelitian ini adalah Watase Uake, sebuah aplikasi lokal yang mampu mengumpulkan, dan menyeleksi literatur 10 tahun terakhir yang paling relevan dengan topik ini, dan semua literatur terindeks scopus dengan peringkat Q1. sampai dengan Q4. Hasil penelitian menunjukkan bahwa dengan menggunakan kata kunci “big data dan manajemen data pertanian” diperoleh 89 literatur, dimana 75 literatur memasuki fase seleksi, dan pada fase retrieval tersisa 47 literatur. Setelah jurnal di-download, kemudian di-upload ke sistem, tersisa 23 artikel yang paling relevan. Berdasarkan keterkaitan kata kunci, pemanfaatan big data dalam manajemen data bidang pertanian lebih banyak untuk menduga produksi pada sistem pertanian presisi, pertanian cerdas, dan sistem pertanian berkelanjutan. Peluang penggunaan big data adalah membantu petani dalam menghemat biaya produksi dan meningkatkan hasil panen mereka melalui analisa iklim, jenis tanah, kandungan nutrisi tanah, dan varietas unggul. Tantangan yang dihadapi malfungsi perangkat, gangguan cuaca, dan masalah keamanan data.

Teks Lengkap:

Download PDF

Referensi


Al-Sai, Z., Husin, M., Syed-Mohamad, S., Abdullah, R., Zitar, R., Abualigah, L., & Gandomi, A. (2023). Big data maturity assessment models: a Systematic literature review. Big Data and Cognitive Computing, 7(1). https://doi.org/10.3390/bdcc7010002

Bernardo, B., Mamede, H., Barroso, J., & dos Santos, V. (2024). Data governance & quality management—Innovation and breakthroughs across different fields. Journal of Innovation and Knowledge, 9(4). https://doi.org/10.1016/j.jik.2024.100598

Bhat, S., & Huang, N. (2021). Big data and AI revolution in precision agriculture: survey and challenges. IEEE Access, 9, 110209–110222. https://doi.org/10.1109/ACCESS.2021.3102227

Bronson, K., & Knezevic, I. (2016). Big data in food and agriculture. Big Data and Society, 3(1), 1–5. https://doi.org/10.1177/2053951716648174

Carbonell, I. (2016). The ethics of big data in big agriculture. Internet Policy Review, 5(1), 1–13. https://doi.org/10.14763/2016.1.405

Cheng, J. (2021). Application of big data analysis to agricultural production, agricultural product marketing and influencing factors in intelligent agriculture. Journal of Computing and Information Technology, 29(3), 151–165. https://doi.org/10.20532/cit.2021.1005404

Clement, R., Lee, H., Manoukis, N., Pacheco, Y., Ross, F., Sisterson, M., & Owen, C. (2025). Addressing biological invasions in agriculture with big data in an informatics age. Agriculture (Switzerland), 15(11), 1–34. https://doi.org/10.3390/agriculture15111157

Gopal, M., & Chintala, B. (2020). Big data challenges and opportunities in agriculture. International Journal of Agricultural and Environmental Information Systems, 11(1), 48–66. https://doi.org/10.4018/IJAEIS.2020010103

Keswani, B., Mohapatra, A., Keswani, P., Khanna, A., Gupta, D., & Rodrigues, J. (2020). Improving weather dependent zone specific irrigation control scheme in IoT and big data enabled self driven precision agriculture mechanism. Enterprise Information Systems, 14(9–10), 1494–1515. https://doi.org/10.1080/17517575.2020.1713406

Krishna, S., Kumar, R., Rose, J., Patidar, V., Soni, A., Mehta, D., & Ranadive, A. (2023). Artificial intelligence and big data analytics-based optimization of crop yields in sustainable agriculture. Carpathian Journal of Food Science and Technology, (Special issue), 1–15. https://doi.org/10.34302/SI/238

Lioutas, E., & Charatsari, C. (2020). Big data in agriculture: does the new oil lead to sustainability? Geoforum, 109(December 2019), 1–3. https://doi.org/10.1016/j.geoforum.2019.12.019

Liu, W. (2022). Application of data visualization and big data analysis in intelligent agriculture. Journal of Computing and Information Technology, 29(4), 251–263. https://doi.org/10.20532/CIT.2021.1005390

Majumdar, J., Naraseeyappa, S., & Ankalaki, S. (2017). Analysis of agriculture data using data mining techniques: application of big data. Journal of Big Data, 4(1), 1–15. https://doi.org/10.1186/s40537-017-0077-4

Misra, N., Dixit, Y., Al-Mallahi, A., Bhullar, M., Upadhyay, R., & Martynenko, A. (2022). IoT, big data, and artificial intelligence in agriculture and food industry. IEEE Internet of Things Journal, 9(9), 6305–6324. https://doi.org/10.1109/JIOT.2020.2998584

Osinga, S., Paudel, D., Mouzakitis, S., & Athanasiadis, I. (2022). Big data in agriculture: Between opportunity and solution. Agricultural Systems, 195(June 2021), 103298. https://doi.org/10.1016/j.agsy.2021.103298

Rao, N. (2018). Big data and climate smart agriculture - Status and implications for agricultural research and innovation in India. In Proceedings of the Indian National Science Academy (Vol. 84, pp. 625–640). https://doi.org/10.16943/ptinsa/2018/49342

Rao, Z., & Yuan, J. (2021). Data mining and statistics issues of precision and intelligent agriculture based on big data analysis. Acta Agriculturae Scandinavica Section B: Soil and Plant Science, 71(9), 870–883. https://doi.org/10.1080/09064710.2021.1954684

Sajib, M., & Sayem, A. (2025). Innovations in sensor-based systems and sustainable energy solutions for smart agriculture: a review. Encyclopedia, 5(2), 67. https://doi.org/10.3390/encyclopedia5020067

Šajnović, U., Vošner, H., Završnik, J., Žlahtič, B., & Kokol, P. (2024). Internet of things and big data analytics inpPreventive healthcare: a synthetic review. Electronics (Switzerland), 13(18). https://doi.org/10.3390/electronics13183642

Tantalaki, N., Souravlas, S., & Roumeliotis, M. (2019). Data-driven decision making in precision agriculture: the rise of big data in agricultural systems. Journal of Agricultural and Food Information, 20(4), 344–380. https://doi.org/10.1080/10496505.2019.1638264

Tseng, F., Cho, H., & Wu, H. (2019). Applying big data for intelligent agriculture-based crop selection analysis. IEEE Access, 7, 116965–116974. https://doi.org/10.1109/ACCESS.2019.2935564

Valencia, O., Johansen, K., Solorio, B., Li, T., Houborg, R., Malbeteau, Y., … McCabe, M. (2020). Mapping groundwater abstractions from irrigated agriculture: Big data, inverse modeling, and a satellite-model fusion approach. Hydrology and Earth System Sciences, 24(11), 5251–5277. https://doi.org/10.5194/hess-24-5251-2020

Villamar-Torres, R., Factos-Laiño, K., Yánez-Cajo, D., Mayorga-Morejon, K., & Jazayeri, S. (2025). An overview to the new era in efficient crop management: artificial intelligence, machine learning, big data, bioinformatics, metagenomics and precision agriculture. The Journal of Animal and Plant Sciences, 35(3), 638–659. https://doi.org/10.36899/japs.2025.3.0054

Wolfert, S., Ge, L., Verdouw, C., & Bogaardt, M. (2017). Big data in smart farming – a review. Agricultural Systems, 153, 69–80. https://doi.org/10.1016/j.agsy.2017.01.023

Young, L., Hyman, M., & Rater, B. (2018). Exploring a big data approach to building a list frame for urban agriculture: a pilot study in the City of Baltimore. Journal of Official Statistics, 34(2), 323–340. https://doi.org/10.2478/jos-2018-0015

Zhenjian, L., Jiahua, L., & Yunbao, X. (2021). Research on the path of agriculture sustainable development based on the concept of circular economy and big data. Acta Agriculturae Scandinavica Section B: Soil and Plant Science, 71(9), 1024–1035. https://doi.org/10.1080/09064710.2021.1929436




DOI: https://doi.org/10.37531/mirai.v10i2.9922

Refbacks

  • Saat ini tidak ada refbacks.


Flag Counter

Creative Commons License

JURNAL MIRAI MANAGEMENT is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Web
Analytics