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Bridging The Digital Divide: Internet Access And Farmer Poverty In East Java

*Dias Satria orcid scopus  -  Universitas Brawijaya, Indonesia
Christiayu Natalia orcid scopus  -  Badan Pusat Statistik Kota Malang, Indonesia
Open Access Copyright 2025 Agrisocionomics: Jurnal Sosial Ekonomi Pertanian under http://creativecommons.org/licenses/by-sa/4.0.

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Abstract

Poverty among farmers remains a structural challenge in agricultural development in Indonesia; low productivity and limited access to information technology are the main problems.  Addressing this issue is crucial for national food security and sustainable rural livelihoods. This study aims to examine the profile of poor farmers and analyze the effect of internet use on the risk of poverty among farmers in East Java Province. The data comes from the March 2023 National Socio-Economic Survey (Susenas) microdata, comprising 21.368 individual observations. The analysis method used is binary logistic regression due to the binary classification of the dependent variable, with model segregation based on urban and rural areas, implemented using Stata software. The results show that poor farmers generally come from the food crop subsector and are concentrated in certain areas such as Madura Island.  Digital literacy and internet utilization are still very low, while access to formal financing is also limited.  Internet access significantly reduces the poverty risk, with users being 2.72 times more likely to be non-poor, especially in urban areas. This study recommends different policy approaches between urban and rural areas to realize inclusive and adaptive agriculture in the digital era.

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Keywords: binary logistic regression, farmer poverty, internet utilization, Susenas

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  1. Alfonsi, R. M., Naidoo, M., & Gasparatos, A. 2024. Adoption and desirable characteristics of Information and Communication Technologies for urban small-scale food producers in South Africa. Frontiers in Sustainable Food Systems, 8. https://doi.org/10.3389/fsufs.2024.1332978
  2. Ambarwati, A., Chazali, C., Huijsmans, R., Sadoko, I., White, B., & Wijaya, H. 2025. Generational Reproduction of Indonesian Smallholder Farming: Cases From Java and Flores. Journal of Agrarian Change. https://doi.org/10.1111/joac.70010
  3. Balehegn, M., Duncan, A., Tolera, A., Ayantunde, A. A., Issa, S., Karimou, M., Zampaligré, N., André, K., Gnanda, I., Varijakshapanicker, P., Kebreab, E., Dubeux, J., Boote, K., Minta, M., Feyissa, F., & Adesogan, A. T. 2020. Improving adoption of technologies and interventions for increasing supply of quality livestock feed in low- and middle-income countries. Global Food Security, 26, 100372. https://doi.org/10.1016/j.gfs.2020.100372
  4. BPS. 2024. Produk Domestik Regional Bruto Provinsi-Provinsi di Indonesia menurut Lapangan Usaha 2019-2023
  5. BPS Provinsi Jawa Timur. 2023. Provinsi Jawa Timur Dalam Angka 2023
  6. Cunha, E. R. da, Santos, C. A. G., Silva, R. M. da, Bacani, V. M., & Pott, A. 2021. Future scenarios based on a CA-Markov land use and land cover simulation model for a tropical humid basin in the Cerrado/Atlantic forest ecotone of Brazil. Land Use Policy, 101, 105141. https://doi.org/10.1016/j.landusepol.2020.105141
  7. Douyon, A., Worou, O. N., Diama, A., Badolo, F., Denou, R. K., Touré, S., Sidibé, A., Nebie, B., & Tabo, R. 2022. Impact of Crop Diversification on Household Food and Nutrition Security in Southern and Central Mali. Frontiers in Sustainable Food Systems, 5. https://doi.org/10.3389/fsufs.2021.751349
  8. Fremmpong, R. B., Gross, E., & Owusu, V. 2023. Crop diversity, sustainable food and nutritional security among smallholder farmers in Ghana. British Food Journal, 125(12), 4372–4395. https://doi.org/10.1108/BFJ-12-2022-1060
  9. Haryanto, T., Wardana, W. W., Jamil, I. R., Brintanti, A. R. D., & Ibrahim, K. H. 2023. Impact of credit access on farm performance: Does source of credit matter? Heliyon, 9(9), e19720. https://doi.org/10.1016/j.heliyon.2023.e19720
  10. Hosmer, D. W., Lemeshow, S., Sturdivant, R. X., & Army Academy, U. S. 2013. Applied Logistic Regression Third Edition. www.wiley.com
  11. Ji, S., & Zhuang, J. 2023. The Impact Path of Digital Literacy on Farmers’ Entrepreneurial Performance: Based on Survey Data in Jiangsu Province. Sustainability, 15(14), 11159. https://doi.org/10.3390/su151411159
  12. Jolliffe, D., & Tetteh-Baah, S. K. 2024. Identifying the poor – Accounting for household economies of scale in global poverty estimates. World Development, 179, 106593. https://doi.org/10.1016/j.worlddev.2024.106593
  13. Kartiasih, F., Djalal Nachrowi, N., Wisana, I. D. G. K., & Handayani, D. 2023. Inequalities of Indonesia’s regional digital development and its association with socioeconomic characteristics: a spatial and multivariate analysis. Information Technology for Development, 29(2–3), 299–328. https://doi.org/10.1080/02681102.2022.2110556
  14. Kosasih, A., & Sulaiman, E. 2024. Digital transformation in rural settings: Unlocking opportunities for sustainable economic growth and community empowerment. Journal of Sustainable Tourism and Entrepreneurship, 5(2), 129–143. https://doi.org/10.35912/joste.v5i2.2278
  15. Mariyono, J., Abdurrachman, H., Suswati, E., Susilawati, A. D., Sujarwo, M., Waskito, J., Suwandi, & Zainudin, A. 2020. Rural modernisation through intensive vegetable farming agribusiness in Indonesia. Rural Society, 29(2), 116–133. https://doi.org/10.1080/10371656.2020.1787621
  16. Mathanda, H., Pangapanga-Phiri, I., Tufa, A., Mangisoni, J., Alene, A., Ngoma, H., Phiri, H. H., & Chikoye, D. 2025. Does social capital influence the intensity of conservation agriculture adoption among smallholder farmers in Malawi? Environmental and Sustainability Indicators, 26, 100630. https://doi.org/10.1016/j.indic.2025.100630
  17. Meng, X., Yang, S., & Pan, G. 2024. Innovation practices in agricultural transformation in East China: Exploring the impact and implications of the new professional farmer training model. Heliyon, 10(14), e34671. https://doi.org/10.1016/j.heliyon.2024.e34671
  18. Mgale, Y. J., & Yunxian, Y. 2021. Price risk perceptions and adoption of management strategies by smallholder rice farmers in Mbeya region, Tanzania. Cogent Food & Agriculture, 7(1). https://doi.org/10.1080/23311932.2021.1919370
  19. Moahid, M., & Maharjan, K. L. 2020. Factors Affecting Farmers’ Access to Formal and Informal Credit: Evidence from Rural Afghanistan. Sustainability, 12(3), 1268. https://doi.org/10.3390/su12031268
  20. Ngomane, T. 2024. Enhancing Market Access for Female Farmers Through the Nkomazi Farmer Production Support Unit (FPSU) in Mpumalanga, South Africa. Journal of Public Administration and Development Alternatives, 9(2), 87–100. https://doi.org/10.55190/JPADA.2024.328
  21. Nguyen, T.-T., Nguyen, T. T., & Grote, U. 2023. Credit, shocks and production efficiency of rice farmers in Vietnam. Economic Analysis and Policy, 77, 780–791. https://doi.org/10.1016/j.eap.2022.12.018
  22. Rutsaert, P., Chamberlin, J., Oluoch, K. O., Kitoto, V. O., & Donovan, J. 2021. The geography of agricultural input markets in rural Tanzania. Food Security, 13(6), 1379–1391. https://doi.org/10.1007/s12571-021-01181-9
  23. Sargani, G. R., Wang, B., Leghari, S. J., & Ruan, J. 2025. Is digital transformation the key to agricultural strength? A novel approach to productivity and supply chain resilience. Smart Agricultural Technology, 10, 100838. https://doi.org/10.1016/j.atech.2025.100838
  24. Thilakarathne, N. N., Abu Bakar, M. S., Abas, P. E., & Yassin, H. 2025. Internet of things enabled smart agriculture: Current status, latest advancements, challenges and countermeasures. Heliyon, 11(3), e42136. https://doi.org/10.1016/j.heliyon.2025.e42136
  25. Twumasi Ankrah, M., Asante, D., Wang, P., Ntiamoah, E. B., & Jiang, Y. 2023. Can the use of the internet improve fish farmers’ financial performance? Evidence from Ghana. Marine Policy, 149, 105494. https://doi.org/10.1016/j.marpol.2023.105494
  26. Xiao, Y., Yin, M., Wang, H., & Xiang, Y. 2025. Digital Finance, Digital Usage Divide, and Urban–Rural Income Gap: Evidence from China. Systems, 13(3), 145. https://doi.org/10.3390/systems13030145
  27. Xie, H., Zhang, J., & Shao, J. (2023). Difference in the influence of internet use on the relative poverty among farmers with different income structures. Economic Analysis and Policy, 78, 561–570. https://doi.org/10.1016/j.eap.2023.03.022
  28. Yimam, D. A., & Holvoet, N. (2024). Unpacking the invisible complex realities: intersections of gender and marital status in determining the intrinsic vulnerability of smallholder farmers to climate change in Northwestern Ethiopia. Climate and Development, 16(6), 502–513. https://doi.org/10.1080/17565529.2023.2246038
  29. Zhai, S., Peng, C., & Sheng, Y. (2023). Assessing the impact of digital financial inclusion on agricultural total factor productivity in China. International Food and Agribusiness Management Review, 26(3), 519–534. https://doi.org/10.22434/IFAMR2022.0132
  30. Zhao, H., Zheng, X., & Yang, L. (2022). Does Digital Inclusive Finance Narrow the Urban-Rural Income Gap through Primary Distribution and Redistribution? Sustainability, 14(4), 2120. https://doi.org/10.3390/su14042120
  31. Zheng, H., & Ma, W. (2024). Economic benefits of internet use for smallholder wheat farmers. Applied Economics, 56(4), 398–413. https://doi.org/10.1080/00036846.2023.2167928

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