Analisis Adopsi dan Penggunaan Aplikasi Pertanian Digital oleh Petani Skala Kecil di Kabupaten Tuban dengan Model UTAUT

Maruli Tua Sihombing; Musa Hubeis; Eko Ruddy Cahyadi

doi:10.29244/mikm.19.2.78-90

Maruli Tua Sihombing Program Studi Ilmu Manajemen, FEM IPB
Musa Hubeis Departemen Manajemen, Fakultas Ekonomi dan Manajemen IPB
Eko Ruddy Cahyadi Departemen Manajemen, Fakultas Ekonomi dan Manajemen IPB

DOI: https://doi.org/10.29244/mikm.19.2.78-90

Keywords: adoption, digital farming applications, smallholder farmers

Abstract

The agricultural sector, as the cornerstone of food security in Indonesia, is predominantly managed by smallholder farmers who are still accustomed to conventional methods. The challenges of climate change will affect the upstream agricultural industry, necessitating farmers to digitally transform their operations to enhance productivity. Digital-based agricultural applications have been introduced by several technology service developers to farmers, but their adoption rates are still relatively low. One common model used to study the acceptance and use of technology is the Unified Theory of Acceptance and Use of Technology (UTAUT). The UTAUT model has not been widely applied in Indonesia, specifically among smallholder farmers with specific characteristics. This research aims to analyze the factors influencing the intention and behavior of smallholder farmers to adopt and use digital agricultural application technology using the UTAUT model. The research was conducted from March to April 2024 in the agricultural hub region of Tuban Regency, with 124 smallholder farmers as respondents, using purposive sampling technique. This research utilized a descriptive data analysis method based on cross-tabulation with an SEM-PLS approach. The findings indicate that performance expectations, effort expectations, and facilitation conditions collectively influence the behavior of using digital agricultural applications through farmers' behavioral intentions. Differences in age levels were found to moderate the relationship among variables. Younger farmers need to be fully engaged in utilizing the dissemination of digital agricultural application technology through training practices supported by improved facilities

Downloads

Download data is not yet available.

References

[BPS] Badan Pusat Statistik. 2022. Indikator tujuan pembangunan berkelanjutan dan karakteristik utama sektor pertanian (Hasil survei pertanian terintegrasi 2021). Jakarta (ID): Badan Pusat Statistik.
[BPS] Badan Pusat Statistik. 2023. Berita resmi statistik: Keadaan ketenagakerjaan Indonesia Agustus 2023. Jakarta (ID): Badan Pusat Statistik.
[BPS] Badan Pusat Statistik. 2023. Hasil pencacahan lengkap sensus pertanian 2023 Tahap I – Sensus Pertanian 2023. Jakarta (ID) : Badan Pusat Statistik.
[M Corps] Mercy Corps Agrifin, Rabo Foundation. 2020. Final report: Landscaping of digital agricultural system of Indonesia.
Ahikiriza E, Wesana J, Huylenbroeck GV et al. 2022. Farmer knowledge and the intention to use smartphone-based information management technologies in Uganda. Computers and Electronics in Agriculture. 202 107413; 1 -13. doi: 10.1016/j.compag.2022.107413.
Ajzen I, Madden TJ. 1986. Prediction of goal-directed behavior: attitudes, intentions, and perceived behavioral control. Journal of Experimental Social Psychology, 22 (5); 453–474. doi: 10.1016/0022-1031(86)90045-4.
Chong AY. 2013. Mobile commerce usage activities: The roles of demographic and motivation variables. Technological Forecasting and Social Change, Elsevier. 80(7); 1350-1359. doi: 10.1016/j.techfore.2012.12.011.
Davis F. 1989. Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3); 319-339. doi: 10.2307/249008.
Fanadzo, Morris, Ncube, Bongani. (2018). Challenges and opportunities for revitalising smallholder irrigation schemes in South Africa. Water SA. 44. doi: 10.4314/wsa.v44i3.11.
Filho WL, Fedoruk M, Eustachio JH, Barbir J et al. 2023. How the War in Ukraine Affects Food Security. Foods 12 (21); 1-21. doi: 10.3390/foods122113996.
Fox G, Mooney J, Rosati. 2021. AgriTech Innovators: A Study of Initial Adoption and Continued Use of a Mobile Digital Platform by Family-Operated Farming Enterprises. Agriculture, 11(1283). doi: 10.3390/ agriculture11121283.
Ghozali I. 2011. Structural Equation Modeling Metode Alternatif dengan partial Least Square. Semarang (ID): Universitas Diponegoro.
Li J, Liu G, Chen Y. et al. 2023. Study on the influence mechanism of adoption of smart agriculture technology behavior. Scientific Reports. 13 (8554); 1-11. doi: 10.1038/s41598-023-35091-x.
Lin D, Fu, Xie K et al. 2023. Research on the Improvement of Digital Literacy for Moderately Scaled Tea Farmers under the Background of Digital Intelligence Empowerment. Agriculture. 13; 2-26. doi: 10.3390/agriculture13101859.
Loukis E, Charalabidis Y, Androutsopoulou A. 2016. Promoting open innovation in the public sector through social media monitoring. Government Information Quarterly. 34 (1); 99-109. doi: 10.1016/j.giq.2016.09.004.
Maturano MJ, Verhulst N, Tur-Cardona J, Güereña DT et al. 2021. Understanding Smallholder Farmers’ Intention to Adopt Agricultural Apps: The Role of Mastery Approach and Innovation Hubs in Mexico. Agronomy. 11(194). doi: 10.3390/ agronomy11020194.
Moore GC, Benbasat I. 1991. Development of an instrument to measure the perceptions of adopting an Information Technology Innovation. Information System Research. 2 (3); 173-191. doi: 10.1287/isre.2.3.192.
Pallant J. 2005. SPSS Survival Manual: A step by step guide to data analysis using SPSS for Windows (Version 12).
Putra YH, Warlina L, Fatimah D et al. 2023. Adoption of the Agriculture Application by Farmers Using the UTAUT2 Method Focused on Community Behavior and User Experience. International Journal of Computer Sciences and Mathematics Engineering. 2(2); 52-65. doi: 10.61306/ijecom.v2i2.22.
Rogers EM. 1962. Diffusion of innovations. New York [US]: Free Press
Rogers EM. 2003. Diffusion of innovations 5th Edition. New York [US]: Free Press
Ronaghi MH, Forouharfar A. 2020. A contextualized study of the usage of the Internet of things (IoTs) in smart farming in a typical Middle Eastern country within the context of Unified Theory of Acceptance and Use of Technology model (UTAUT). Technology in Society. 63 (101415); 1-6. doi: 10.1016/j.techsoc.2020.101415.
Thompson RL, Higgins CA, Howell JM. 1991. Personal computing: Toward a conceptual model of utilization. MIS Q Manag Inf Syst. 15(1):125–142. doi:10.2307/249443.
Toretti A, Bratu M, Muller E, Oliveira I, Zampieri M et al. 2022. Advancing near-real-time quality controls of meteorological observations. Bulletin of the American Meteorological Society, 103 (4); 1078-1087. doi: 10.1175/BAMS-D-21-0171.1.
Triandini E, Wijaya IG, Suniantara IK, Wulandari R et al. 2022. Analysis adoption of information technology using the UTAUT method on off-taker poultry farmers in Indonesia. [prosiding] International Conference on Industrial Engineering and Operations Management. 2023 Mar 7-9; Manila, Philippines. IEOM Society International.
Triandis HC. 1979. Values, attitudes, and interpersonal behavior. [simposium]. Nebraska Symposium on Motivation. 27; 195-259.
Usakli A, Kucukergin KG. 2018. Using partial least squares structural equation modeling in hospitality and tourism. Journal of Contemporary Hospitally Management. 30(11): 3462 - 3512. doi: 10.1108/IJCHM-11-2017-0753.
Venkatesh V, Morris M, Davis G, Davis F. 2003. User acceptance of information technology: Toward a unified view. MIS Quarterly, 27(3); 425-478.
Wang J, Zhang S, Zhang L. 2023. Intelligent Hog Farming Adoption Choices Using the Unified Theory of Acceptance and Use of Technology Model: Perspectives from China’s New Agricultural Managers. Agriculture. 13 (2067); 1-22. doi: 10.3390/agriculture13112067.
Williams, MD, Rana NP, Dwivedi YK. 2015. The unified theory of acceptance and use of technology (UTAUT): A literature review. J. Enterp. Inf. Manag. 20 (28); 443-488. doi: 10.1108/JEIM-09-2014-0088.