Have a personal or library account? Click to login
Smart Farming in Indonesia: Behavioural Study on Adoption of Internet-Based Fertilisation Systems Cover

References

  1. APRIYANA, Y. – SURMAINI, E. – ESTININGTYAS, W. – PRAMUDIA, A. – RAMADHANI, F. – SUCIANTINI, S. – SUSANTI, E. – PURNAMAYANI, R. – SYAHBUDDIN, H. 2021. The integrated cropping calendar information system: A coping mechanism to climate variability for sustainable agriculture in Indonesia. In Sustainability, vol. 13, no. 11, article no. 6495. DOI: https://doi.org/10.3390/su13116495
  2. ARRUBLA-HOYOS, W. – OJEDA-BELTRÁN, A. – SOLANO-BARLIZA, A. – RAMBAUTH-IBARRA, G. – BARRIOS-ULLOA, A. – CAMA-PINTO, D. – ARRABAL-CAMPOS, F. M. – MARTÍNEZ-LAO, J. A. – CAMA-PINTO, A. – MANZANO-AGUGLIARO, F. 2022. Precision agriculture and sensor systems applications in Colombia through 5G networks. In Sensors, vol. 22, no. 19, article no. 7295. DOI: https://doi.org/10.3390/s22197295
  3. BAGHERI, A. – TARIGHI, J. – EMAMI, N. – SZYMANEK, M. 2024. Extension experts’ intentions to use precision agricultural technologies, a test with the technology acceptance model. In Acta Technologica Agriculturae, vol. 27, no. 2, pp. 84–91. DOI: https://doi.org/10.2478/ata-2024-0012
  4. BARNES, A. P. – SOTO, I. – EORY, V. – BECK, B. – BALAFOUTIS, A. – SÁNCHEZ, B. – VANGEYTE, J. – FOUNTAS, S. – VAN DER WAL, T. – GÓMEZ-BARBERO, M. 2019. Exploring the adoption of precision agricultural technologies: A cross regional study of EU farmers. In Land Use Policy, vol. 80, pp. 163–174. DOI: https://doi.org/10.1016/j.landusepol.2018.10.004
  5. BURESH, R. J. – CASTILLO, R. L. – DELA TORRE, J. C. – LAURELES, E. V. – SAMSON, M. I. – SINOHIN, P. J. – GUERRA, M. 2019. Site-specific nutrient management for rice in the Philippines: Calculation of field-specific fertilizer requirements by Rice Crop Manager. In Field Crops Research, vol. 239, pp. 56–70. DOI: https://doi.org/10.1016/j.fcr.2019.05.013
  6. GEORGE, D. – MALLERY, P. 2016. IBM SPSS Statistics 23 Step by Step: A Simple Guide and Reference. 14th ed. New York : Routledge, 400 pp. ISBN 9781315545899. DOI: https://doi.org/10.4324/9781315545899
  7. GIRSANG, S. S. – CASTILLO, R. L. – SYAM, M. – ZAINI, Z. – KARTAATMADJA, S. – SUYAMTO – TORRE, J. C. D. – PABUAYON, I. L. B. – LIMPIADA, R. A. – WALUYO – HELMI – SAMIJAN – BUDIONO, R. – HATTA, M. – NURHAYATI – KAMANDALU, N. B. – SUSANTO, B. – PARHUSIP, D. – ABIDIN, Z. – BURESH, R. J. 2025. Site-specific nutrient management for rice using soil properties to adjust phosphorus and potassium supply from compound NPK fertilizer. In Field Crops Research, vol. 326, article no. 109864. DOI: https://doi.org/10.1016/j.fcr.2025.109864
  8. GRÖZINGER, N. – IRLENBUSCH, B. – LASKE, K. – SCHRÖDER, M. 2020. Innovation and communication media in virtual teams – An experimental study. In Journal of Economic Behavior & Organization, vol. 180, pp. 201–218. DOI: https://doi.org/10.1016/j.jebo.2020.09.009
  9. HAIR, J. F. – BLACK, W. C. – BABIN, B. J. – ANDERSON, R. E. 2019. Multivariate_Data_Analysis. 8th ed. Hampshire : Cengage Learning EMEA, 832 pp. ISBN 978-1-4737-5654-0. Available at: https://eli.johogo.com/Class/CCU/SEM/_Multivariate%20Data%20Analysis_Hair.pdf
  10. MISHRA, N. – BHANDARI, N. – MARASENI, T. – DEVKOTA, N. – KHANAL, G. – BHUSAL, B. – BASYAL, D. K. – PAUDEL, U. R. – DANUWAR, R. K. 2024. Technology in farming: Unleashing farmers’ behavioral intention for the adoption of agriculture 5.0. In PLOS ONE, vol. 19, no. 8, article no. e0308883. DOI: https://doi.org/10.1371/journal.pone.0308883
  11. NUGROHO, A. D. 2021. Agricultural market information in developing countries: A literature review. In Agricultural Economics, vol. 67, no. 11, pp. 468–477. DOI: https://doi.org/10.17221/129/2021-AGRICECON
  12. PIERPAOLI, E. – CARLI, G. – PIGNATTI, E. – CANAVARI, M. 2013. Drivers of precision agriculture technologies adoption: A literature review. In Procedia Technology, vol. 8, pp. 61–69. DOI: https://doi.org/10.1016/j.protcy.2013.11.010
  13. RACHMAN, B. – ARININGSIH, E. – SUDARYANTO, T. – ARIANI, M. – SEPTANTI, K. S. – ADAWIYAH, C. R. – ASHARI – AGUSTIAN, A. – SALIEM, H. P. – TARIGAN, H. – SYAHYUTI – YUNIARTI, E. 2022. Sustainability status, sensitive and key factors for increasing rice production: A case study in West Java, Indonesia. In PLoS ONE, vol. 17, no. 12, article no. e0274689. DOI: https://doi.org/10.1371/journal.pone.0274689
  14. RICHTER, N. F. – HAUFF, S. – RINGLE, C. M. – GUDERGAN, S. P. 2022. The use of partial least squares structural equation modeling and complementary methods in international management research. In Management International Review, vol. 62, pp. 449–470. DOI: https://doi.org/10.1007/s11575-022-00475-0
  15. SALIMI, M. – POURDARBANI, R. – NOURI, B. A. 2020. Factors affecting the adoption of agricultural automation using Davis’s acceptance model (case study: Ardabil). In Acta Technologica Agriculturae, vol. 23, no. 1, pp. 30–39. DOI: https://doi.org/10.2478/ata-2020-0006
  16. 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. – WALUYO – SUPARWOTO – YUSTISIA – SUDARMAJI. 2023. Assessing the challenges and opportunities of agricultural information systems to enhance farmers’ capacity and target rice production in Indonesia. In Sustainability, vol. 15, no. 2, article no. 1114. DOI: https://doi.org/10.3390/su15021114
  17. TAMA, R. A. Z. – YING, L. – MARK, M. Y. – HOQUE, M. M. – ADNAN, K. M. – SARKER, S. A. 2021. Assessing farmers’ intention towards conservation agriculture by using the extended theory of planned behavior. In Journal of Environmental Management, vol. 280, article no. 111654. DOI: https://doi.org/10.1016/j.jenvman.2020.111654
  18. TAN, Y. – YING, X. – GAO, W. – WANG, S. – LIU, Z. 2023. Applying an extended theory of planned behavior to predict willingness to pay for green and low-carbon energy transition. In Journal of Cleaner Production, vol. 387, article no. 135893. DOI: https://doi.org/10.1016/j.jclepro.2023.135893
  19. TENENHAUS, M. – AMATO, S. – ESPOSITO VINZI, V. 2004. A global goodness-of-fit index for PLS structural equation modelling. In Proceedings of the XLII SIS (Italian Statistical Society) Scientific Meeting, Vol. Contributed Papers. Padova, Italy : CLEUP, pp. 739–742. Available at: https://www.sis-statistica.org/old/htdocs/files/pdf/atti/RSBa2004p739-742.pdf
  20. WANG, Y. – WANG, Z. – ZHAO, M. – LI, B. 2024. The influence of technology perceptions on farmers’ water-saving irrigation technology adoption behavior in the North China Plain. In Water Policy, vol. 26, no. 2, pp. 170–188. DOI: https://doi.org/10.2166/wp.2024.170
  21. WENG, F. – LIU, X. – HUO, X. 2023. Impact of Internet use on farmers’ organic fertilizer investment: A new perspective of access to credit. In Agriculture, vol. 13, no. 1, article no. 219. DOI: https://doi.org/10.3390/agriculture13010219
Language: English
Page range: 197 - 203
Published on: Nov 3, 2025
Published by: Slovak University of Agriculture in Nitra
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2025 Susilawati, Setia Sari Girsang, Pandu Laksono, Arlyna Budi Pustika, Yanti Rina Darsani, Dorkas Parhusip, Twenty Liana, Amelia Sebayang, Agus Suprihatin, Indra Sakti, Hasil Sembiring, Alfonso Sitorus, Jeannette Maryanty Lumban Tobing, Tommy Purba, Taufik Iqbal Ramdhani, Yudha Purbawa, Novia Chairuman, published by Slovak University of Agriculture in Nitra
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.