Preparing for Indonesian Agricultural Transformation in The Society Era 5.0

Mercy Bientri Yunindanova


Indonesia is an agricultural country with one of its main incomes from the agricultural sector. Indonesia's position in the equatorial region and tropical climate favors Indonesia as a country with megabiodiversity. Indonesia has a variety of regional conditions with agricultural management techniques according to the needs of farmers in the region. Agricultural technology is the key to agricultural transformation, marking changes in each era, including the era of society 5.0. Agriculture in the Society 5.0 era will blend technology with automation, where technology can play a role in replacing and complementing agricultural activities. This set of technologies will allow farmers to control agricultural commodities and their environment. Agricultural activities are carried out using IoT (Internet of Things), AI (Artificial Intelligence), Big Data, and robotic technology. Agriculture in the Society 5.0 era was based on smart agriculture with the concept of precision farming. Indonesia has a great opportunity to be ready to face agriculture in the era of Society 5.0. through 7 TTPS (7 Stages of Transformation of Agriculture Society 5.0) namely Commitment and Policy, Human resources, Research, Data management, Transition, Tools, and Cyber protection. With the right and gradual transformation process, as well as the ability to integrate and synergize across disciplines and across institutions, the transformation process will be able to run well.


agricultural technology; farmer; globalization

Full Text:



Ananda, A. R. 2021. Smart Farming 4.0: masa depan pertanian Indonesia.

Ardiyanti, H. 2014. Cyber-security dan tantangan pengembangannya di Indonesia. Politica Vol. 5 No. 1: 95-110.

Bakala, H.S., Singh, G., and Srivastava, P. 2020. Smart breeding for climate resilient agriculture. In book: Plant Breeding - Current and Future ViewsPublisher: IntechOpen. doi: 10.5772/intechopen.94847

Beckford, G.L. 1973. Persistent poverty: underdevelopment in plantation economies of the third world. The Economic Journal. 83(332):1321-1324.

Chang, C.L. and Lin, K.M. 2018. Smart agricultural machine with a computer vision-based weeding and variable-rate irrigation scheme. Robotics 7, 38; doi:10.3390/robotics7030038.

Fuadi, M., Sutiarso, L., Radi, Virgawati, S., and Nugraheni, P.H.T. 2019. Design of liquid fertilizer applicator based on variable rate application (VRA) for soybean. IOP Conf. Series: Earth and Environmental Science 355 (2019) 012009 IOP Publishing. doi:10.1088/1755-1315/355/1/012009.

Husemann, C. & Novkovic, N. 2014. Farm management information systems: a case study on a German multifunctional farm. Ekonomika Poljoprivrede 61(2):441-453. doi: 10.5937/ekoPolj1402441H

Khadatkar, A., Mathur, S.M., and Gaikwad, B.B. 2018. Automation in transplanting: a smart way of vegetable cultivation. Current Science, 115, 10.

Kremer M. 1993. Population growth and technological change: one million B.C. to 1990. Q J Econ. 108(3):681-716.

Menteri Pertanian. 2021. Diakes pada

OECD. 2012. How is technology changing demand for human skills?” in Lessons from PISA for Japan. OECD Publishing. Paris. doi:

Ogidan, O.K., Onile, A.E., Adegboro, O.G. 2019. Smart irrigation system: a water management procedure. Agricultural Sciences. 10, 25-31. doi: 10.4236/as.2019.101003

Pamungkas, S. 2019. Sistem smart greenhouse pada tanaman paprika berbasis Internet of Things. Telekontran, 7, 2. doi 10.34010/telekontran.v7i2.2277.

Perez-Ruiz, M., Slaughter, D., Fathallah, F., Gliever, C., Miller, B. 2014. Co-robotic intra-row weed control system. Biosyst. Eng. 126, 45–55.

Permadi, Y., Prayogo, S.S., Kusuma, T.M. 2021. Robot edukasi pertanian agrobot-i: rancangan elektronika dan sistem penggerak. Jurnal Ilmiah Informatika Komputer. 26: 1. doi:

Santoso, D.W. dan Hariyanto, K. 2017. Pengembangan sistem penyemprotan pada platform pesawat tanpa awak berbasis quadcopter untuk membantu petani mengurangi biaya pertanian dalam mendorong konsep pertanian pintar (smart farming). Jurnal Ilmiah Bidang Teknologi. Angkasa. ix(2): 49-56.

Shibusawa, S. 2003. Precision farming Japan model. Agricultural Information Research 12(2):125-132. doi: 10.3173/air.12.125.

Sims, B. & Heney, J. 2017. Promoting smallholder adoption of conservation agriculture through mechanization services. Agriculture 7, 64.

Yost, R., Attanandana, T., Colfer, C.J.P., Itoga, S. 2011. Decision support systems in agriculture: some successes and a bright future. In book: Efficient Decision Support Systems - Practice and Challenges from Current to Future. SourceInTech. doi: 10.5772/16380