Digital Readiness and Extension Support in Chili Farmers' Plantix Adoption for Pest Control in Indonesia

Putri Aulia Wardani (1), Gunawan Gunawan (2), Arum Pratiwi (3)
(1) Department of Sustainable Agricultural Extension, Agriculture Development Polytechnic Malang, Indonesia
(2) Department of Sustainable Agricultural Extension, Agriculture Development Polytechnic Malang, Indonesia
(3) Department of Sustainable Agricultural Extension, Agriculture Development Polytechnic Malang, Indonesia
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How to cite (AJARCDE) :
Wardani, P. A., Gunawan, G., & Pratiwi, A. (2026). Digital Readiness and Extension Support in Chili Farmers’ Plantix Adoption for Pest Control in Indonesia. AJARCDE (Asian Journal of Applied Research for Community Development and Empowerment), 10(3), 347–354. https://doi.org/10.29165/ajarcde.v10i3.1264

Digital transformation in agriculture has encouraged the development of artificial intelligence-based applications such as Plantix, which assists farmers in diagnosing plant pests and diseases through image analysis. Although Plantix has proven technically effective, its adoption rate among Indonesian farmers remains low and is presumably influenced by internal and external factors that have not been widely studied at the local level. This study aims to analyze the factors influencing chili farmers' adoption of the Plantix application in Kayukebek Village, Indonesia. A quantitative approach was used with 58 respondents selected through purposive sampling from a population of 188 chili farmers. Data were analyzed using multiple linear regression with two independent variables: farmer characteristics (age, education, farming experience, smartphone use frequency) and environmental support and interaction (extension support, access to information and training, social influence, internet access). The results show that the regression model explains 45.5% of the variation in Plantix adoption (R² = 0.455) and is significant simultaneously (F = 5.118; p < 0.001). Partially, smartphone use frequency, agricultural extension support, and social and environmental influence significantly affect adoption (p < 0.05), while age, education, farming experience, information/training access, and internet access do not. These findings indicate that adoption is driven more by digital readiness, extension assistance, and peer influence than by farmers' demographic characteristics or the availability of infrastructure alone, and provide a basis for designing more targeted extension strategies.


Contribution to Sustainable Development Goals (SDGs):


SDG 1: No Poverty
SDG 2: Zero Hunger
SDG 8: Decent Work and Economic Growth
SDG 9: Industry, Innovation and Infrastructure
SDG 12: Responsible Consumption and Production

[1] C. Giua, V. C. Materia, and L. Camanzi, “Smart farming technologies adoption: Which factors play a role in the digital transition?,” Elsevier Technol. Soc., vol. 68, no. 101869, 2022, doi: https://doi.org/10.1016/j.techsoc.2022.101869.

[2] B. Wijayanto and E. Puspitojati, “Optimizing Agricultural Mechanization to Enhance The Efficiency and Productivity of Farming In Indonesia: A Review,” AJARCDE (Asian J. Appl. Res. Community Dev. Empower., vol. 8, no. 3, pp. 209–217, 2024, doi: 10.29165/ajarcde.v8i3.493.

[3] E. M. Rogers, “Diffusion of Innovations (5th ed.). Free Press.,” 2003.

[4] M. Shoaib, A. Sadeghi-Niaraki, F. Ali, I. Hussain, and S. Khalid, “Leveraging deep learning for plant disease and pest detection: a comprehensive review and future directions,” Front. Plant Sci., vol. 16, no. February, pp. 1–19, 2025, doi: 10.3389/fpls.2025.1538163.

[5] A. C. Hampf, C. Nendel, S. Strey, and R. Strey, “Biotic Yield Losses in the Southern Amazon , Brazil?: Making Use of Smartphone-Assisted Plant Disease Diagnosis Data,” Front. Plant Sci., vol. 12, no. April, pp. 1–16, 2021, doi: 10.3389/fpls.2021.621168.

[6] A. Siddiqua, M. A. Kabir, T. Ferdous, I. B. Ali, and L. A. Weston, “Evaluating Plant Disease Detection Mobile Applications: Quality and Limitations,” Agronomy, vol. 12, no. 8, 2022, doi: 10.3390/agronomy12081869.

[7] S. M. Prestiana, D. Padmaningrum, and Sugihardjo, “Peran Penyuluh sebagai Agent of Change dalam Adopsi Inovasi Padi Rojolele Srinuk,” JIA (Jurnal Ilm. Agribisnis) J. Agribisnis dan Ilmu Sos. Ekon. Pertan., vol. 8(3), no. 105, pp. 176–185, 2023.

[8] N. V. Bontsa, A. Mushunje, and S. Ngarava, “Factors Influencing the Perceptions of Smallholder Farmers towards Adoption of Digital Technologies in Eastern Cape Province, South Africa,” Agriculture, vol. 13 (8), p. 1471, 2023, doi: https://doi.org/10.3390/agriculture13081471.

[9] alya septianing dewi Putri, D. . p Lubis, and T. Aulia, “Literasi Digital Anggota Kelompok Wanita Tani dan Pemanfaatannya sebagai Akses Informasi Pertanian Digital Literacy of Women Farmers Group Members and Its Utilization as Access to Agricultural Information,” J. Sains Komun. dan Pengemb. Masy., vol. 08, no. 03, pp. 55–66, 2025, doi: https://doi.org/10.29244/jskpm.v8i03.1408.

[10] Z. Sirajuddin and P. L. Kamba, “Persepsi Petani terhadap Implementasi Teknologi Informasi dan Komunikasi dalam Penyuluhan Pertanian Farmer ’ s Perception on Information and Communication Technology Implementation in Agricultural Extension,” J. Penyul., vol. 17, no. 02, pp. 136–144, 2021, doi: https://journal.ipb.ac.id/index.php/jupe/article/download/32676/22001.

[11] C. Sugihono, S. S. Hariadi, and S. P. Wastutiningsih, “Integrasi Pemanfaatan Teknologi Informasi dan Komunikasi untuk Meningkatkan Layanan Penyuluhan Pertanian,” J. Penyul., vol. 20, no. 02, pp. 178–190, 2024, doi: https://journal.ipb.ac.id/index.php/jupe/article/download/50736/28920.

[12] Z. Ren, Z. Fu, and K. Zhong, “The influence of social capital on farmers ’ green control technology adoption behavior,” Front. Psychol., no. October, pp. 1–14, 2022, doi: 10.3389/fpsyg.2022.1001442.

[13] N. C. Irawan, J. H. Mulyo, A. Suryantini, U. G. Mada, and U. G. Mada, “Unleashing the Power of Digital Farming?: Local Young Farmers ’ Perspectives on Sustainable Value Creation,” Agrar. J. Agribus. Rural Dev. Res., vol. 9, no. 2, pp. 316–333, 2023, doi: https://doi.org/10.18196/agraris.v9i2.239.

[14] M. S. Rahman et al., “Does internet use make farmers happier?? Evidence from Indonesia Does internet use make farmers happier?? Evidence from Indonesia,” Cogent Soc. Sci., vol. 9, no. 2, 2023, doi: 10.1080/23311886.2023.2243716.

[15] A. Kolapo and A. J. Didunyemi, “Effects of exposure on adoption of agricultural smartphone apps among smallholder farmers in Southwest , Nigeria?: implications on farm ? level ? efficiency,” Agric. Food Secur., vol. 13:31, pp. 1–20, 2024, doi: 10.1186/s40066-024-00485-1.

[16] Z. Huang, J. Zhuang, and S. Xiao, “Impact of Mobile Internet Application on Farmers ’ Adoption and Development of Green Technology,” Sustainability, vol. 14, no. 16745, 2022, doi: https://doi.org/10.3390/su142416745.

[17] A. J. Lamm and K. W. Lamm, “Using Non-Probability Sampling Methods in Agricultural and Extension Education Research,” J. Int. Agric. Ext. Educ., vol. 26, no. 1, pp. 52–59, 2019, doi: 10.5191/iaee.2019.26105.

[18] H. G. Hoang and H. D. Tran, “Smallholder farmers ’ perception and adoption of digital agricultural technologies?: An empirical evidence from Vietnam,” Outlook Agric., vol. 52 (4), pp. 457–468, 2023, doi: 10.1177/00307270231197825.

[19] L. D. Willis, “Formulating the Research Question and Framing the Hypothesis,” Respir. Care, vol. 68, no. 8, pp. 1180–1185, 2023, doi: 10.4187/respcare.10975.

[20] M. Salam et al., “The causal-effect model of input factor allocation on maize production: Using binary logistic regression in search for ways to be more productive,” J. Agric. Food Res., vol. 16, no. February, p. 101094, 2024, doi: 10.1016/j.jafr.2024.101094.

[21] G. Mardiatmoko, “Pentingnya Uji Asumsi Klasik pada Analisis Regresi Linier Berganda (Studi Kasus Penyusunan Persamaan Allometrik Kenari Muda [Canarium Indicum L.]),” Barekeng (Jurnal Ilmu Mat. dan Ter., vol. 14, no. 3, pp. 333–342, 2020, doi: https://doi.org/10.30598/barekengvol14iss3pp333-342.

[22] A. Q. Sari, Y. L. Sukestiyarno, and A. Agoestanto, “Batasan Prasyarat Uji Normalitas dan Uji Homogenitas pada Model Regresi Linear,” Unnes J. Math., vol. 6, no. 2, pp. 168–177, 2017.

[23] V. Lasdun, A. P. Harou, C. Magomba, and D. Guereña, “Peer learning and technology adoption in a digital farmer-to-farmer network,” J. Dev. Econ., vol. 176, pp. 0–56, 2025, doi: 10.1016/j.jdeveco.2025.103496.

[24] S. Coggins et al., “How have smallholder farmers used digital extension tools? Developer and user voices from Sub-Saharan Africa, South Asia and Southeast Asia,” Glob. Food Sec., vol. 32, no. December 2021, p. 100577, 2022, doi: 10.1016/j.gfs.2021.100577.

[25] D. Landmann, C. Johan, and L. Verena, “Determinants of Small ? Scale Farmers ’ Intention to Use Smartphones for Generating Agricultural Knowledge in Developing Countries?: Evidence from Rural India,” Eur. J. Dev. Res., vol. 33, no. 6, pp. 1435–1454, 2021, doi: 10.1057/s41287-020-00284-x.

[26] H. D. Bancin, R. Agnesia, M. Sirait, S. Sugiardi, and W. Kalimantan, “Breaking Barriers To Digital Adoption: A Case Study Of Paddy Farmers In West Kalimantan,” Agrisep Kaji. Masal. Sos. Ekon. Pertan. dan Agribisnis, vol. 25, no. 02, pp. 757–776, 2025, doi: https://doi.org/10.31186/jagrisep.24.02.757-776.

[27] V. Knitsch, L. Daniel, and J. Welz, “Mapping varieties of farmers ’ experience in the digital transformation?: a new perspective on transformative dynamics,” Precis. Agric., vol. 25, no. 4, pp. 1958–1981, 2024, doi: 10.1007/s11119-024-10148-7.

[28] D. Steur, N. Onek, W. Odongo, H. De Steur, and C. Management, “Unraveling heterogeneity in Farmers ’ adoption of Mobile Phone Technologies?: A systematic review .,” Technol. Forecast. Soc. Change, vol. 185, no. 122048., pp. 1–34, 2022, doi: https://doi.org/10.1016/j.techfore.2022.122048.

[29] C. Jack, A. H. Adenuga, A. Ashfield, and M. Wallace, “Investigating the drivers of farmers’ engagement in a participatory extension programme: The case of Northern Ireland business development groups,” Sustain., vol. 12, no. 11, 2020, doi: 10.3390/su12114510.

[30] I. Siffana, U. Romadi, and Gunawan, “Efektivitas Program Pembangunan PSP terhadap Etos Kerja Petani Desa Ngadisuko , Kabupaten Trenggalek , Jawa Timur,” J. Penyul., vol. 17, no. 02, pp. 177–193, 2021, doi: https://doi.org/10.25015/17202131948.

[31] Jumadin, Gunawan, and Lisa Navitasari, “Penyuluhan Pemanfaatan Pestisida Nabati Daun Sirih (Piper betle L.) untuk Menangani Kutu Daun (Aphis sp.) pada Cabai Merah,” J. Sustain. Agric. Ext., vol. 2, no. 2, pp. 65–73, 2024, doi: 10.47687/josae.v2i2.974.

[32] F. D. Davis, “Information Technology Introduction,” MIS Q., vol. 13, no. 3, pp. 319–340, 2014.

[33] M. Michels and O. Musshoff, “An Empirical Study of Smartphone Use Intensity in German Agriculture,” Ger. J. Agric. Econ., vol. 69, no. 2, pp. 127–142, 2020, doi: https://doi.org/10.30430/69.2020.2.127-142.

[34] M. Michels and O. Musshoff, “A tobit regression model for the timing of smartphone adoption in agriculture,” Heliyon, vol. 8, no. 11, p. e11272, 2022, doi: 10.1016/j.heliyon.2022.e11272.

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