Skip to main content
Log in

Are Indonesian rice farmers ready to adopt precision agricultural technologies?

  • Published:
Precision Agriculture Aims and scope Submit manuscript

Abstract

Precision agriculture technologies (PATs) are believed to be able to ensure the sustainability of rice production. However, the adoption of PATs in developing countries is much lower than in developed countries. The basic question of our research is how Indonesian rice farmers are ready to adopt precision agriculture since they are smallholder farmers. Data was collected from 521 rice farmers in five Indonesian provinces, i.e. North Sumatra, West Java, Yogyakarta, South Sulawesi, and East Nusa Tenggara, in 2023. Farmers were interviewed face to face using structured questionnaires. The data were analysed using Partial Least Squares-Structural Equation Modelling (PLS-SEM) through the Python software. The results showed that Indonesian rice farmers have a moderate level of readiness. The mean value of the capabilities and opportunities indicators were 2.54 to 3.8, while the range for the opportunity’s indicator is 3.23 to 4.11, larger than the capabilities indicators. The level of precision agriculture implementation on Indonesian rice farmers was significant influenced by management (β = 0.42, t = 7.11, p < 0.05), environment (β = 0.17, t = 3.63, p < 0.05), readiness (β = 0.14, t = 2.51, p < 0.05), and technology (β = 0.10, t = 2.12, p < 0.05), economy (β = 0.09, t = 3.63, p < 0.05), and technology2 (β = -0.072, t = 3.5, p < 0.05). Meanwhile, farmer readiness was significantly influenced by opportunity (β = 0.39, t = 6.64, p < 0.05) and capabilities (β = 0.43, t = 6.82, p < 0.05). This research provides information on the status of human resource capacity in exploiting opportunities for implementing precision agriculture and technical policy advice. The Indonesian government should improve farmers’ skills in information technology, Global Positioning Systems (GPS), and sensor technology in agricultural sectors, and facilitate access to technology and resources in order to increase rice farmers’ readiness to adopt PATs. For opportunity indicators, however, further research is needed to determine which components require immediate attention for construction or development.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  • Adrian, A. M., Norwood, S. H., & Mask, P. L. (2005). Producers’ perceptions and attitudes toward precision agriculture technologies. Computers and Electronics in Agriculture, 48(3), 256–271. https://doi.org/10.1016/J.COMPAG.2005.04.004.

    Article  Google Scholar 

  • Akhter, R., & Sofi, S. A. (2022). Precision agriculture using IoT data analytics and machine learning. Journal of King Saud University - Computer and Information Sciences, 34(8), 5602–5618. https://doi.org/10.1016/J.JKSUCI.2021.05.013.

    Article  Google Scholar 

  • Amarnath, G., Simons, G., Alahacoon, N., Smakhtin, V., Sharma, B., Gismalla, Y., Mohammed, Y., & Andriessen, M. (2018). Using smart ICT to provide weather and water information to smallholders in Africa: The case of Gash River Basin, Sudan. Climate Risk Management, 22, 52–66. https://doi.org/10.1016/j.crm.2018.10.001.

    Article  Google Scholar 

  • Amrullah, E. R., & Pullaila, A. (2020). The impact of combine harvester on loss of rice yields in Banten Province). Jurnal Agro Ekonomi, 37(2), 113. https://doi.org/10.21082/jae.v37n2.2019.113-122(in Indonesian).

    Article  Google Scholar 

  • Annosi, C. M., Brunetta, F., Monti, A., & Nati, F. (2019). Is the trend your friend? An analysis of technology 4.0 investment decisions in agricultural SMEs. Computers in Industry 109 (2019)59–71. https://doi.org/10.1016/j.compind.2019.04.003.

  • Arrubla-Hoyos, W., Ojeda-Beltrán, A., Solano-Barliza, A., Rambauth-Ibarra, G., Barrios-Ulloa, A., Cama-Pinto, D., Arrabal-Campos, F., Martinez-Lao, J., Cama-Pinto, A., & Manzano-Agugliaro, F. (2022). Precision agriculture and sensor systems applications in Colombia through 5G networks. Sensors (Basel, Switzerland), 22(19), 1–22. https://doi.org/10.3390/s22197295.

    Article  Google Scholar 

  • Arya, N. N., & Mahaputra, I. K. (2020). Analysis of determining factor for adoption of integrated crop management of lowland paddy using partial least square. Informatika Pertanian, 29(1), 1–12.

    Article  Google Scholar 

  • Aubert, B. A., Schroeder, A., & Grimaudo, J. (2012). IT as anabler of sustainable farming: An empirical analysis of farmers’ adoption decision of precision agriculture technology. Decision Support Systems, 54(1), 510–520. https://doi.org/10.1016/j.dss.2012.07.002.

    Article  Google Scholar 

  • Awotide, B. A., Karimov, A. A., & Diagne, A. (2016). Agricultural technology adoption, commercialization and smallholder rice farmers’ welfare in rural Nigeria. Agricultural and Food Economics, 4(1), 1–24. https://doi.org/10.1186/s40100-016-0047-8.

    Article  Google Scholar 

  • Bado, V. B., Djaman, K., & Mel, V. C. (2018). Developing fertilizer recommendations for rice in Sub-saharan Africa, achievements and opportunities. Paddy and Water Environment, 16(3), 571–586. https://doi.org/10.1007/s10333-018-0649-8.

    Article  Google Scholar 

  • Balafoutis, A. T., van Evert, F. K., & Fountas, S. (2020). Smart farming technology trends: Economic and environmental effects, labor impact, and adoption readiness. Agronomy, 10(5), 1–26. https://doi.org/10.3390/agronomy10050743.

    Article  CAS  Google Scholar 

  • Balittanah. (2004). User Manual of paddy soil test kit version 1.0. Indonesian Ministry of Agriculture (1st ed.). Balitbangtan. Jakarta. Indonesia.

  • Barnes, A., De Soto, I., Eory, V., Beck, B., Balafoutis, A., Sánchez, B., Vangeyte, J., Fountas, S., van der Wal, T., & Gómez-Barbero, M. (2019). Influencing factors and incentives on the intention to adopt precision agricultural technologies within arable farming systems. Environmental Science and Policy, 93, 66–74. https://doi.org/10.1016/j.envsci.2018.12.014.

    Article  Google Scholar 

  • Blasch, J., van der Kroon, B., van Beukering, P., Munster, R., Fabiani, S., Nino, P., & Vanino, S. (2022). Farmer preferences for adopting precision farming technologies: A case study from Italy. European Review of Agricultural Economics, 49(1), 33–81. https://doi.org/10.1093/erae/jbaa031.

    Article  Google Scholar 

  • Blut, M., & Wang, C. (2020). Technology readiness: A meta-analysis of conceptualizations of the construct and its impact on technology usage. Journal of the Academy of Marketing Science, 48(4), 649–669. https://doi.org/10.1007/s11747-019-00680-8.

    Article  Google Scholar 

  • BPS-Statistic Indonesia (2023). Complete enumeration results of the 2023 cencus of Agriculture.

  • Calle, M., Watson, A., Lai, J., & Porter, W. A. (2022). Opportunity alertness, risk-taking and diversification by small- and medium-sized farmers. Journal of Developmental Entrepreneurship, 27(02), 2250015. https://doi.org/10.1142/S1084946722500157.

    Article  Google Scholar 

  • Connor, M., de Guia, A. H., Pustika, A. B., Sudarmaji, Kobarsih, M., & Hellin, J. (2021). Rice Farming in Central Java, Indonesia—Adoption of Sustainable Farming Practices, Impacts and Implications. Agronomy 2021, 11, 881. https://doi.org/10.3390/agronomy11050881.

  • Connor, M., Malabayabas, A. J. B., de Guia, A. H., Wehmeyer, H., Pame, A. R. P., Htwe, N. M., Zhong, X., Fu, Y., Liang, K., Pan, J., Hu, X., Liu, Y., Subekti, N. A., Sembiring, H., Pustika, A. B., Sudarmaji, Hutapea, Y., Raharjo, B., Girsang, S. S., Syahri, Girsang, M. A., Sumantri, R. U., Widyayanti, S., Singleton, G. R., & Tuan, L. A. (2023). Environmental, Social, and Economic Challenges in Lowland Rice Production. In: Closing Rice Yield Gaps in Asia Innovations, Scaling, and Policies for Environmentally Sustainable Lowland Rice Production (Eds. Connor, M., Gummert, M., & Singleton, G.R.). Springer. 284 p.

  • Constantin, A. M. (2012). The antecedents of E-Satisfaction and E-Loyalty and the relationship between them. Timisoara Journal of Economics, 18, 236–252. https://www.researchgate.net/publication/260047377.

    Google Scholar 

  • Daum, T., Adegbola, P. Y., Adegbola, C., Daudu, C., Issa, F., Kamau, G., Kergna, A. O., Mose, L., Ndirpaya, Y., Fatunbi, O., Zossou, R., Kirui, O., & Birner, R. (2022). Mechanization, digitalization, and rural youth - stakeholder perceptions on three mega-topics for agricultural transformation in four African countries. Global Food Security, 32, 1–10. https://doi.org/10.1016/j.gfs.2022.100616.

    Article  Google Scholar 

  • Denkyirah, E., Adu, D., Aziz, A., Denkyirah, E., & Okoffo, E. (2016). Analysis of the factors influencing smallholder rice farmers’ access to credit in the upper east region of Ghana. Asian Journal of Agricultural Extension Economics & Sociology, 10(4), 1–11. https://doi.org/10.9734/ajaees/2016/24768.

    Article  Google Scholar 

  • Duang-Ek-Anong, S., Pibulcharoensit, S., & Phongsatha, T. (2019). Technology readiness for internet of things (IoT) adoption in smart farming in Thailand. International Journal of Simulation: Systems Science & Technology. https://doi.org/10.5013/ijssst.a.20.05.12.

    Article  Google Scholar 

  • Ehlers, M. H., Finger, R., El Benni, N., Gocht, A., Sørensen, C. A. G., Gusset, M., Pfeifer, C., Poppe, K., Regan, A., Rose, D. C., Wolfert, S., & Huber, R. (2022). Scenarios for European agricultural policymaking in the era of digitalisation. Agricultural Systems 196 (2022) 103318, https://doi.org/10.1016/j.agsy.2021.103318.

  • Erythrina. (2016). Leaf Color Chart: A Tool to increase Nitrogen Fertilizer Efficiency in Rice. Jurnal Penelitian Dan Pengembangan Pertanian, 35(1), 1–10.

    Article  Google Scholar 

  • Fadhliani, Z., Author, C., & Gadjah Mada, U. (2022). Indonesian rice farm households’ perceived effect of COVID-19 pandemic. Jurnal Agribest, 6, 47–52. https://doi.org/10.32528/agribest.v6i1.7137.

    Article  Google Scholar 

  • Gebbers, R., & Adamchuk, V. I. (2010). Precision agriculture and food security. Science, 327(5967), 828–831. https://doi.org/10.1126/science.1183899.

    Article  CAS  PubMed  Google Scholar 

  • Goud, R. B., Tripathi, R., Guru, P. K., Mohanty, S., Kumar, A., Khanam, R., Munda, S., Vijayakumar, S., Debnath, M., Sivashankari, M., Kumar, K., Mohapatra, S. D., & Nayak, A. K. (2022). Advanced techniques for precision farming in rice. In P. Bhattacharyya, K. Chakraborty, K. A. Molla, A. Poonam, D. Bhaduri, R. P. Sah, S. Paul, P. S. Hanjagi, G. Basana-Gowda, & P. Swain (Eds.), Climate resilient technologies for Rice Based Production systems in Eastern India. ICAR-National Rice Research Institute.

  • Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2014). A primer on partial least squares structural equation modeling (PLS-SEM) (1st ed., Vol. 1). Sage Production.

  • Hair, J. F. H., Hult, G. T. M., Ringle, C. M., Sarstedt, M., Danks, N. P., & Ray, S. (2022). Partial Least Squares Structural Equation Modelling (PLS-SEM) using R. Springer. https://doi.org/10.1007/978-3-030-80519-7.

  • Hamrita, T. K. (2021). In T. K. Future, & Hamrita (Eds.), Women in Precision Agriculture Technological breakthroughs, challenges and aspirations Forra Prosperous and sustainable (Vol. 1). Springer. https://doi.org/10.1007/978-3-030-49244-1.

  • Heryanda, K. K., Ayesha, I., & Adha, R. (2021). Improvement of farmers’ competency for agriculture progress. International Journal of Multidisciplinary Research and Analysis, 4(3), 245–253. https://doi.org/10.3390/agriculture14010099.

    Article  Google Scholar 

  • Hidayat, A. S., & Lesmana, T. (2011). The development of Organic Rice Farming in Indonesia. Review of Indonesian Economic and Business Studies, 2(1), 71–87.

    Google Scholar 

  • Ho, T. D. N., Kuwornu, J. K. M., & Tsusaka, T. W. (2022). Factors influencing smallholder rice farmers’ vulnerability to climate change and variability in the Mekong Delta Region of Vietnam. European Journal of Development Research, 34(1), 272–302. https://doi.org/10.1057/s41287-021-00371-7.

    Article  Google Scholar 

  • ISPA (2021). Precision Ag Definition. https://www.ispag.org/ (last accessed on March 10th, 2023).

  • Jarrar, Y., Awobamise, A. O., & Sellos, P. S. (2020). Technological readiness index (TRI) and the intention to use smartphone apps for tourism: A focus on indubai mobile tourism app. International Journal of Data and Network Science, 4(3), 297–304. https://doi.org/10.5267/j.ijdns.2020.6.003.

    Article  Google Scholar 

  • Kaloxylos, A., Groumas, A., Sarris, V., Katsikas, L., Magdalinos, P., Antoniou, E., Politopoulou, Z., Wolfert, S., Brewster, C., Eigenmann, R., & Maestre Terol, C. (2014). A cloud-based farm management system: Architecture and implementation. Computers and Electronics in Agriculture, 100, 168–179. https://doi.org/10.1016/J.COMPAG.2013.11.014.

    Article  Google Scholar 

  • Kendall, H., Clark, B., Li, W., Jin, S., Jones, G. D., Chen, J., Taylor, J., Li, Z., & Flewer, L. J. (2022). Precision Agriculture technology adoption: A qualitative study of small-scale commercial ‘family farms’ located in the North China Plain. Precision Agriculture, 1–33. https://doi.org/10.1007/s11119-021-09839-2.

  • Klerkx, L., Jakku, E., & Labarthe, P. (2019). A review of social science on digital agriculture, smart farming and agriculture 4.0: New contributions and a future research agenda. Wageningen Journal of Life Sciences 90–91 (2019) 100315. https://doi.org/10.1016/j.njas.2019.100315.

  • Kotler, P., Bowen, J. T., & Makens, J. C. (2014). Marketing for hospitality and tourism (6th ed.). Person.

  • Kurniawan, F. E. (2021). The dilemma of agricultural mechanization and the marginalization of women farmworkers in rural areas. Sodality: Jurnal Sosiologi Pedesaan, 9(2). https://doi.org/10.22500/9202132575.

  • Lawson, L. G., Pedersen, S. M., Sørensen, C. G., Pesonen, L., Fountas, S., Werner, A., & Blackmore, S. (2011). A four-nation survey of farm information management and advanced farming systems: A descriptive analysis of survey responses. Computers and Electronics in Agriculture, 77(1), 7–20. https://doi.org/10.1016/j.compag.2011.03.002.

    Article  Google Scholar 

  • Lee C.-L., Strong R., Briers G., Murphrey T., Rajan N., Rampold S. (2023). A correlational study of two U.S. state extension professionals’ behavioral intentions to improve sustainable food chains through precision farming practices. Foods, 12(11), 2208. https://doi.org/10.3390/foods12112208.

  • Lencsés, E., Takács, I., & Takács-György, K. (2014). Farmers’ perception of precision farming technology among Hungarian farmers. Sustainability, 6(12), 8452–8465. https://doi.org/10.3390/su6128452.

    Article  Google Scholar 

  • Li, Q., Zeng, F., Mei, H., Li, T., & Li, D. (2019). Roles of motivation, opportunity, ability, and trust in the willingness of farmers to adopt green fertilization techniques. Sustainability, 11(24), 6902. https://doi.org/10.3390/su11246902.

    Article  Google Scholar 

  • Li, W., Clark, B., Taylor, J. A., Kendall, H., Jones, G., Li, Z., Jin, S., Zhao, C., Yang, G., Shuai, C., Cheng, X., Cheng, J., Yange, H., & Frewer, L. J. (2020). A hybrid modelling approach to understanding adoption of precision agriculture technologies in Chinese cropping systems. Computers and Electronics in Agriculture, 172(2020), 105305. https://doi.org/10.1016/j.compag.2020.105305.

    Article  Google Scholar 

  • Liu, D., Chen, H., Geng, T., Shi, Q., & Chen, W. (2022). The impact of individual capabilities on the access to ecosystem services: A case study from the Loess Plateau, China. Environmental Science and Pollution Research, 29(7), 10443–10455. https://doi.org/10.1007/s11356-021-16486-7.

    Article  PubMed  Google Scholar 

  • Lowenberg-DeBoer, J., & Erickson, B. (2019). Setting the record straight on precision agriculture adoption. Agronomy Journal, 111(4), 1552–1569. https://doi.org/10.2134/agronj2018.12.0779.

    Article  Google Scholar 

  • Maat, H. (2016). Encyclopaedia of the History of Science, Technology, and Medicine in NonWestern Cultures. Encycl. Hist. Sci. Technol. Med. Non-Western Cult.

  • Magesa, M. M., Michael, K., & Ko, J. (2020). Access and use of agricultural market information by smallholder farmers: Measuring informational capabilities. The Electronic Journal of Information System in Developing Countries, 86(6), e12134. https://doi.org/10.1002/isd2.12134.

    Article  Google Scholar 

  • Managanta, A. A. (2020). The role of agricultural extension in increasing competence and income rice farmers’. Indonesian Journal of Agricultural Research, 3(2), 77–88. https://doi.org/10.32734/injar.v3i2.3963.

    Article  Google Scholar 

  • Mandal, S. K., & Maity, A. (2013). Precision farming for small agricultural farm: Indian scenario. American Journal of Experimental Agriculture, 3(1), 200–2017.

    Article  Google Scholar 

  • Mardiharini, M., Jamal, E., Rohaeni, E. S., Indrawanto, C., Indraningsih, K. S., Gunawan, E., Ramadhan, R. P., Fahmid, I. M., Wardana, Ï. P., & Ariningsih, E. (2023). Indonesian rice farmers’ perceptions of different sources of information and their effect on farmer capability. Open Agriculture, 8(1), 1–16. https://doi.org/10.1515/opag-2022-0200.

    Article  Google Scholar 

  • Masganti, M., Susilawati, A., & Yuliani, N. (2020). Optimizing land use to increase rice production in South Kalimantan. Jurnal Sumberdaya Lahan, 14(2), 101. https://doi.org/10.21082/jsdl.v14n2.2020.101-114(in Indonesian).

    Article  Google Scholar 

  • Masi, M., De Rosa, M., Vecchio, Y., Bartoli, L., & Adinolfi, F. (2022). The long way to innovation adoption: Insights from precision agriculture. Agricultural and Food Economics, 10(1), 1–17. https://doi.org/10.1186/s40100-022-00236-5.

    Article  Google Scholar 

  • Maulana, H., & Kanai, H. (2020). Development of Precision Agriculture Models for Medium and Small-Scale Agriculture in Indonesia. INCITEST 2020. IOP Conf. Series: Materials Science and Engineering 879 (2020) 012085. https://doi.org/10.1088/1757-899X/879/1/012085.

  • McCampbell, M., Adewopo, J., Klerkx, L., & Leeuwis, C. (2021). Are farmers ready to use phone-based digital tools for agronomic advice? Ex-ante user readiness assessment using the case of Rwandan banana farmers. Journal of Agricultural Education and Extension, 29(1), 29–51. https://doi.org/10.1080/1389224X.2021.1984955.

    Article  Google Scholar 

  • McFadden, J., Njuki, E., & Griffin, T. (2023). Precision agriculture in the digital era: Recent adoption in the U.S farms. Economic Information Bulletin, 248. Economic Research Service. U.S Department of Agriculture.

  • Methorst, R. G. (Ron), Roep, D., Dirk), Verhees, F. J. H. M., Frans, Verstegen, J. A. A. M., & Jos (Eds.). (2017). Differences in farmers’ perception of opportunities for farm development. NJAS - Wageningen Journal of Life Sciences, 81, 9–18. https://doi.org/10.1016/J.NJAS.2017.02.001.

  • Michailidis, A., Charatsari, C., Bournaris, T., & Loizhou, E. (2024). A first view on the competencies and training needs of farmers’ working with and researchers’ working on precision sgriculture technologies. Agriculture, 14(99), 1–12. https://doi.org/10.3390/agriculture14010099.

    Article  Google Scholar 

  • Michels, M., Fecke, W., Feil, J., Musshoff, O., Lülfs-Baden, F., & Krone, S. (2020). Anytime, anyplace, anywhere – a sample selection model of mobile internet adoption in German agriculture. Agribusiness, 36(2), 192–207. https://doi.org/10.1002/agr.21635.

    Article  Google Scholar 

  • Ministry of Agriculture (2018). Agricultural Statistics; Susanti, A.A., Waryanto, B., Eds.; Center for Agricultural Data and Information System (Ministry of Agriculture): Jakarta, Indonesia.

  • Ministry of Agriculture of the Republic of Indonesia. (2022). Agricultural infrastructure and facilities statistics 2017–2021. Jakarta. Indonesia. (Issue ton).

  • Mucharam, I., Rustiadi, E., Fauzi, A., & Harianto (2020). Assessment of rice farming sustainability: Evidence from Indonesia provincial data. International Journal of Sustainable Development and Planning, 15(8), 1323–13332. https://doi.org/10.18280/ijsdp.150819.

    Article  Google Scholar 

  • Muhibuddin, Amanah, S., & Sadono, D. (2015). Agribusiness competencies of Smallholders with Vegetable planting in Banda Aceh and Aceh Besar. Jurnal Penyuluhan, 11(2), 186–200. https://doi.org/10.25015/penyuluhan.v11i2.10582.

    Article  Google Scholar 

  • Nurliza, N., Dolorosa, E., Hamid, A., & Yusra, A. (2017). Farming performance of Rice Farmer for Sustainable Agriculture and Food Security in West Kalimantan. AGRARIS: Journal of Agribusiness and Rural Development Research, 3(2), 84–92. https://doi.org/10.18196/agr.3248.

    Article  Google Scholar 

  • Nuryanti, S., Dewa, D., & Swastika, K. S. (2011). Roles of Farmers’ groups in Agricultural Technology Adoption. Forum Penelitian Agro Ekonomi, 29(2), 115–128.

    Article  Google Scholar 

  • Obagbemi, S. D., Bamidele, J., Bako, H., Alabuja, F. O., Ajayi, A. H., & Sennuga, S. O. (2022). Effects of Micro-credit Scheme on Rice Production among Smallholder Farmers in Kwali Area Council, Abuja. European Journal of Business and Management Research, 7(6), 26–34. https://doi.org/10.24018/ejbmr.2022.7.6.1666.

    Article  Google Scholar 

  • Ofori, M., & El-Gayar, O. (2021). Drivers and challenges of precision agriculture: A social media perspective. Precision Agriculture, 22(3), 1019–1044. https://doi.org/10.1007/s11119-020-09760-0.

    Article  Google Scholar 

  • Pathak, V., Verma, V., Rawat, B., Kaur, B., Babu, N., Sharma, A., Dewali, S., Yadav, M., Kumari, R., Singh, S., Mohapatra, A., Pandey, V., Rana, N., & Cunill, J. (2022). Current status of pesticide effects on environment, human health and it’s eco-friendly management as bioremediation: A comprehensive review. Frontiers in Microbiology, 13, 1–29. https://doi.org/10.3389/fmicb.2022.962619.

    Article  Google Scholar 

  • Paustian, M., & Theuvsen, L. (2017). Adoption of precision agriculture technologies by German crop farmers. Precision Agriculture, 18(5), 701–716. https://doi.org/10.1007/s11119-016-9482-5.

    Article  Google Scholar 

  • Pfeiffer, J., Gabriel, A., & Gandorfer, M. (2021). Klein gegen Groß–Vergleich von klein-und großstrukturierten Agrarregionen beim Einsatz digitaler Technologien [Small vs. large-comparison of small- and large-scale agricultural regions in the use of digital technologies]. In: Meyer-Aurich, A., Gandorfer, M., Hoffmann, C., Weltzien, C., Belluingrath-Kimura, S., & Floto H. (Eds.), Informations- und Kommunikationstechnologie in kritischen Zeiten. (pp. 247–252). Gesellschaft für Informatik.

  • Pickthall, T., Trivett, E., Grove, I., & Kennedy, R. (2017). An investigation into the barriers that prevent the adoption of precision farming technologies in combinable cropping in the UK (p. 135). Aspects of applied biology.

  • Poudel, U., Kattel, R., Gurung, B., Shrestha, S., & Paudel, A. (2021). Economic analysis of rice (Oryza sativa L.) cultivation in Gorkha district of Nepal. Archives of Agriculture and Environmental Science, 6(4), 489–497. https://doi.org/10.26832/24566632.2021.0604011.

    Article  Google Scholar 

  • Pratiwi, R. D., Salman, D., & Mujahidin, I. (2022). Digitalization of agriculture through the kostratani program on rice field agribusiness in Barebbo District, Bone Regency. Jurnal Sosial Ekonomi Pertanian, 18(3), 277–292. https://doi.org/10.20956/jsep.v18i3.22358.

    Article  Google Scholar 

  • Purnawan, E., Brunori, G., & Prosperi, P. (2022). Small family farms, a review in Indonesian context. International Journal of Multidisciplinary: Applied Business and Education Research, 3(12), 2708–2725. https://doi.org/10.11594/ijmaber.03.12.23.

    Article  Google Scholar 

  • Quince, E. (2015). Summary of Indonesia’s agriculture, natural resources, and environment sector assessment. ADB Pap Indones, 8, 1–7.

    Google Scholar 

  • Radoglou-Grammatikis, P., Sarigiannidis, P., Langkas, T., & Moscholios, I. (2020). A compilation of UAV applications for precision agriculture. Computer Networks, 172. https://doi.org/10.1016/j.comnet.2020.107148.

  • Rahman, I. A., Memon, A. H., & Karim, A. T. A. (2013). Examining factors affecting budget overrun of construction projects undertaken through management procurement method using PLS-sem approach. Procedia - Social and Behavioral Sciences, 107, 120–128. https://doi.org/10.1016/j.sbspro.2013.12.407.

    Article  Google Scholar 

  • Ramadhani, F., Runtunuwu, E., & Syahbuddin, H. (2013). Information technology systems of integrated cropping calendar. Informatika Pertanian, 22(2), 103–112.

    Article  Google Scholar 

  • Raza, A., Tong, G., Sikandar, F., Erokhin, V., & Tong, Z. (2023). Financial literacy and credit accessibility of rice farmers in Pakistan: Analysis for Central Punjab and Khyber Pakhtunkhwa regions. Sustainability (Switzerland), 15(4). https://doi.org/10.3390/su15042963.

  • Rola-Rubzen, M. F., Paris, T., Hawkins, J., & Sapkota, B. (2020). Improving gender participation in agricultural technology adoption in Asia: From rhetoric to practical action. Applied Economic Perspectives and Policy, 42(1), 113–125. https://doi.org/10.1002/aepp.13011.

    Article  Google Scholar 

  • Ruzzante, S., Labarta, R., & Bilton, A. (2021). Adoption of agricultural technology in the developing world: A meta-analysis of the empirical literature. World Development, 146. https://doi.org/10.1016/j.worlddev.2021.105599.

  • Santoso, A. B., Girsang, S. S., Raharjo, B., Pustika, A. B., Hutapea, Y., Kobarsih, M., Suprihatin, A., Manurung, E. D., Siagian, D. R., Hanapi, S., Purba, T., Parhusip, D., Budiarti, S. W., Wanita, Y. P., Hatmi, R. U., Girsang, M. A., & Haloho, L. (2023). Waluyo, Suparwoto, Yustisia, & Sudarmaji (2023). Assessing the challenges and Opportunities of Agricultural Information Systems to Enhance Farmers’ Capacity and Target Rice production in Indonesia. Sustainability, 15, 1114. https://doi.org/10.3390/su15021114.

    Article  Google Scholar 

  • Sarasso, G., Sarasso, R., Finassi, A., & Masoero, G. (2019). Rice yield advances under precision agriculture: A farm lesson. Journal of Agronomy Research, 1(4), 10–21. https://doi.org/10.14302/issn.2639-3166.jar-19-2691.

    Article  Google Scholar 

  • Sarkar, A., Azim, J. A., Asif, A., Al, Qian, L., & Peau, A. K. (2021). Structural equation modelling for indicators of sustainable agriculture: Prospective of a developing country’s agriculture. Land Use Policy, 109. https://doi.org/10.1016/j.landusepol.2021.105638.

  • Shannon, D. K., Clay, D. E., & Sudduth, K. A. (2018). An introduction to precision agriculture. In D.K. Shannon, D.E. Clay, & N.R. Kitchen (Eds.), Precision Agriculture Basics (pp. 1–12). https://doi.org/10.2134/precisionagbasics.2016.0084.

  • Sishodia, R., Ray, R., & Singh, S. (2020). Applications of remote sensing in precision agriculture: A review. Remote Sensing, 12(19), 1–31. https://doi.org/10.3390/rs12193136.

    Article  Google Scholar 

  • Suganda, M. R., Rangga, K. K., & Listiana, I. (2020). Perceptions of rice farmers on the utilization of combine harvester assistance in gadingrejo subdistrict, pringsewu regency. Jurnal Agribisnis Terpadu, 13(1), 154. https://doi.org/10.33512/jat.v13i1.7541(in Indonesia).

    Article  Google Scholar 

  • Syafruddin, Utama, I. M. S., Yasa, I. G. W. M., Marhaeni, A., & A. I., N. (2018). Effect of socio-economic and demographic factors against social capital, farming performance and farmers welfare in Sumbawa, Indonesia. IOSR Journal of Economics and Finance, 9(1), 1–08. https://doi.org/10.9790/5933-0901040108.

    Article  Google Scholar 

  • Syaifudin, A. R. M., Shah, M. S., Teoh, C. C., Aufa, B. M., Nadzim, N. M., Radzi, F. Z. F., Najib, M. Y. M., Zamzuri, C. S. F., Hassan, D. A., & Haffiez, A. S. M. (2016). Variable rate application of fertilizer in rice precision farming. International Conference on Agricultural and Food Engineering, 227–281. https://www.researchgate.net/publication/332060576.

  • Tayari, E., Jamshid, A., & Goodarzi, H. (2015). Role of GPS and GIS in precision agriculture. Journal of Scientific Research and Development, 2(3), 157–162.

    Google Scholar 

  • Tey, Y. S., & Brindal, M. (2022). A meta-analysis of factors driving the adoption of precision agriculture. Precision Agriculture, 23(2), 353–372. https://doi.org/10.1007/s11119-021-09840-9.

    Article  Google Scholar 

  • Thorburn, C. (2015). The rise and demise of integrated pest management in rice in Indonesia. Insects, 6(2), 381–408. https://doi.org/10.3390/insects6020381.

    Article  PubMed Central  Google Scholar 

  • Tripathi, R., Kumar, A., Guru, P., Debnath, M., Mohapatra, S., Mohaanty, S., Khanam, R., Shahid, M., & Nayak, A. (2021). Precision farming technologies for water and nutrient management in rice: Challenges and opportunities. Oryza-An International Journal on Rice, 58(Special), 126–142. https://doi.org/10.35709/ory.2021.58.spl.5.

    Article  Google Scholar 

  • Udoumoh, U. I., & Ikrang, E. G. (2021). Precision farming and fertilizer recommendation using geographic information system (GIS): A review. International Journal of Agriculture and Earth Science, 7(2), 68–75.

    Google Scholar 

  • UNDP (2021). Precision Agriculture for Smallholder Farmers. https://www.undp.org/publications/precision-agriculture-smallholder-farmers (last accessed on March 30th, 2023).

  • Utami, A., & Harianto, H. (2021). Farmers’ subsistence in Indonesian rice farming. Jurnal Agribisnis Indonesia, 9(2), 79–87. https://doi.org/10.29244/jai.2021.9.2.79-87.

    Article  Google Scholar 

  • Vecchio, Y., Agnusdei, G., Miglietta, P., & Capitanio, F. (2020). Adoption of precision farming tools: The case of Italian farmers. International Journal of Environmental Research and Public Health, 17(3). https://doi.org/10.3390/ijerph17030869.

  • Vukelić, N., & Rodić, V. (2014). Farmers’ management capacities as a success factor in agriculture: A review. Economics of Agriculture, 61(3), 805–814.

    Google Scholar 

  • Wardani, A. P. Y., & Darmawan, N. A. S. (2020). The role of financial technology in MSMEs: Increasing financial literacy based on payment gateways. Jurnal Ilmiah Akuntansi Dan Humanika, 10(2), 170–175. https://doi.org/10.23887/jiah.v10i2.25947(in Indonesian).

    Article  Google Scholar 

  • Wicaksono, H. (2017). Model of information search among farmers: A case study of farmers in Rowosari Village, Grobogan, Central Java. Orbith, 13(1), 28–35. (in Indonesian).

    Google Scholar 

  • Xiao, S., He, Z., Zhang, W., & Qin, X. (2022). The Agricultural Green Production following the Technological Progress: Evidence from China. International Journal of Environmental Research and Public Health, 19(16), 9876. https://doi.org/10.3390/ijerph19169876.

    Article  PubMed  PubMed Central  Google Scholar 

  • Yarashynskaya, A., & Prus, P. (2022). Precision agriculture implementation factors and adoption potential: The case study of Polish agriculture. Agronomy, 12(9). https://doi.org/10.3390/agronomy12092226.

  • Yatribi, T. (2020). Factors affecting precision agriculture adoption: A systematic literature review. Economics, 8(2), 103–121. https://doi.org/10.2478/eoik-2020-0013.

    Article  Google Scholar 

  • Zaman, N., Raof, W., Saili, A., Aziz, N., Fatah, F., & Vaiappuri, S. (2023). Adoption of smart farming technology among rice farmers. Journal of Advanced Research in Applied Sciences and Engineering Technology, 29(2), 268–275. https://doi.org/10.37934/araset.29.2.268275.

    Article  Google Scholar 

  • Zambon, I., Cecchini, M., Egidi, G., Saporito, M. G., & Colantoni, A. (2019). Revolution 4.0: Industry vs. agriculture in a future development for SMEs. Processes, 7(1), 36. https://doi.org/10.3390/pr7010036.

    Article  Google Scholar 

  • Zhang, N., Wang, M., & Wang, N. (2002). Precision agriculture - a worldwide overview. Computers and Electronics in Agriculture, 36, 113–132. https://doi.org/10.1016/S0168-1699(02)00096-0.

    Article  Google Scholar 

  • Zhou, X., & Ding, D. (2022). Factors influencing farmers’ willingness and behaviors in organic agriculture development: An empirical analysis based on survey data of farmers in Anhui Province. Sustainability (Switzerland), 14(22). https://doi.org/10.3390/su142214945.

Download references

Acknowledgements

The authors would like to acknowledge the help of Mrs Suriani and Mr Nano from Deli Serdang District, Mr Sukirno from Serdang Bedagai District, and Mrs Eva from Simalungun District in North Sumatra Province, Mr Solihin from Sumedang District in West Java Province, Mr H. Khalik from Sidrap District, Mr Ical Tancung from Wajo District, and Sudirman from Pinrang District in South Sulawesi Province for coordinating the questionnaire survey. The research was supported by The Indonesian National Research and Innovation Agency (BRIN).

Author information

Authors and Affiliations

Authors

Contributions

Conceptualization: ABS, ESU, SFB, S, SDI, YS, NS; Methodology: ABS, ESU, SFB, NC, S., SDI, ABP, YS, NS, R, VA; Software: ABS, SFB, NC, S, SDI, ABP, YS, NS, HFPP, WS, NREK; Developing Questionnaire: ABS, ESU, SFB, NC, S, SDI, ABP, YS, NS, R, VA, EDM, HFPP, WS, NREK, DP, W, AM, JMLT; Validation: ABS, ESU, SFB, NC, S, SDI, ABP, YS, NS, R, VA, EDM, HFPP, WS, NREK, DP, AM, JMLT; Formal Analysis: ABS, ESU, SFB, NC, S, SDI, ABP, YS, NS, R, WS, NREK; Investigation: ABS, ESU, SFB, NC, S, SDI, ABP, YS, NS, VA, DP, JMLT; Resources: ABS, ESU, SFB, NC, S, SDI, ABP, YS, NS, R, VA, EDM, HFPP, WS, NREK, DP, W, AM, JMLT; Data Curation: ABS, ESU, SFB, NC, S, SDI, ABP, YS, NS, R, VA, EDM, HFPP, WS, NREK, DP, W, AM, JMLT; Writing Original Draft: ABS, ESU, SFB, NC, S, SDI, ABP, YS, NS, R, VA, EDM, HFPP, WS, NREK, DP, W, AM, JMLT; Writing - Review and Editing: ABS, ESU, SFB, NC, S, SDI, ABP, YS, NS, R, VA, EDM, HFPP, WS, NREK, DP, W, AM, JMLT; Visualization: ABS, ESU, SFB, NC, S, SDI, ABP, YS, NS, R, VA, EDM, HFPP, WS, W, AM; Supervision: ABS, ESU, SFB, NC, S, SDI, ABP, YS, NS, R, VA, EDM, HFPP, W; Project Administration: ESU, NC, ABP, EDM, NREK, DP, W, AM, JMLT; Funding Acquisation: ABS, ESU, SFB, NC, S, SDI, ABP, YS, NS, R, VA, EDM, HFPP, WS, NREK, DP, W, AM, JMLT.

Corresponding author

Correspondence to Evawaty S. Ulina.

Ethics declarations

Conflict of interest

The authors declare no conflict of interest.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Santoso, A.B., Ulina, E.S., Batubara, S.F. et al. Are Indonesian rice farmers ready to adopt precision agricultural technologies?. Precision Agric 25, 2113–2139 (2024). https://doi.org/10.1007/s11119-024-10156-7

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11119-024-10156-7

Keywords

Navigation