Artificial Intelligence-Based Innovation in Improving Agricultural Production and Welfare of Village Farmers in Indonesia

Syaharuddin Syaharuddin, Riana Riana

Abstract


This study aims to explore the potential of artificial intelligence (AI)-based innovation in enhancing agricultural production and the welfare of rural farmers in Indonesia. A systematic literature review method is employed to identify actionable steps to address challenges such as limited access to technology, disparities in the distribution of AI benefits, and the need for improved digital literacy and technical skills among farmers. Literature sources were selected from Scopus, DOAJ, and Google Scholar databases, covering publications from 2014 to 2024. The study findings reveal that the integration of artificial intelligence (AI) technology holds significant transformative potential in Indonesian agriculture, particularly in rural areas. While promising prospects are offered for enhancing efficiency, welfare, and sustainability in agriculture, challenges related to technology accessibility, training, and socio-cultural implications remain significant hurdles that need to be addressed. Collaborative efforts among policymakers, researchers, and agricultural stakeholders are required to maximize the benefits of AI technology in enhancing productivity and welfare among farmers across various rural regions in Indonesia. Urgent research is needed to gain a deeper understanding of effective strategies for improving accessibility and adoption of AI technology among farmers, as well as the socio-cultural implications of AI technology integration in the agricultural context.

Keywords


Artificial Intelligence; Agricultural Innovation.

Full Text:

PDF

References


Abate, G. T., Bernard, T., de Brauw, A., & Minot, N. (2018). The impact of the use of new technologies on farmers’ wheat yield in Ethiopia: evidence from a randomized control trial. Agricultural Economics (United Kingdom). https://doi.org/10.1111/agec.12425

Aini, D. N., Oktavianti, B., Husain, M. J., Sabillah, D. A., Rizaldi, S. T., & Mustakim, M. (2022). Seleksi Fitur untuk Prediksi Hasil Produksi Agrikultur pada Algoritma K-Nearest Neighbor (KNN). Jurnal Sistem Komputer Dan Informatika (JSON). https://doi.org/10.30865/json.v4i1.4813

Ajib, M., & Habiburrahman Aksa, A. (2023). Dampak Perkembangan Teknologi Pertanian Terhadap Perubahan Sosial Masyarakat Petani. Al-I’timad: Jurnal Dakwah Dan Pengembangan Masyarakat Islam. https://doi.org/10.35878/alitimad.v1i1.725

Bayei, J. D., & Nache, A. I. (2014). The Effect Of Socio-Economic Characteristics Of Cattle Farmers On The Adoption Of Artificial Insemination Technology In Kaduna State Of Nigeria. IOSR Journal of Agriculture and Veterinary Science. https://doi.org/10.9790/2380-07921117

Cameron, L., Olivia, S., & Shah, M. (2019). Scaling up sanitation: Evidence from an RCT in Indonesia. Journal of Development Economics. https://doi.org/10.1016/j.jdeveco.2018.12.001

Chulwa, A. Z., Ibad, M. Z., & Tanjung, A. S. (2022). Dampak Digitalisasi Pertanian Terhadap Tingkat Ekonomi Masyarakat Petani Di Kecamatan Adiluwih Dan Gadingrejo Pringsewu. Jurnal Perencanaan Dan Pengembangan Kebijakan. https://doi.org/10.35472/jppk.v2i3.845

Darmono, Yogatama, A., Ma’ruf, K., Setiyawa, B. P., & Fadlullah, Y. A. (2023). Optimization of Agricultural Technology with Irrigation Control in Rice Plants Based on Internet of Things. Indonesian Journal of Advanced Research. https://doi.org/10.55927/ijar.v2i5.4149

Dwi Indriyanti, A. (2022). Design and Build Smart Agriculture Using Cognitive Internet of Things (C IoT). Journal Research of Social Science, Economics, and Management, 1(7), 922–930. https://doi.org/10.59141/jrssem.v1i7.113

Elbasi, E., Mostafa, N., Alarnaout, Z., Zreikat, A. I., Cina, E., Varghese, G., Shdefat, A., Topcu, A. E., Abdelbaki, W., Mathew, S., & Zaki, C. (2023). Artificial Intelligence Technology in the Agricultural Sector: A Systematic Literature Review. In IEEE Access. https://doi.org/10.1109/ACCESS.2022.3232485

Eli-Chukwu, N. C. (2019). Applications of Artificial Intelligence in Agriculture: A Review. Engineering, Technology and Applied Science Research. https://doi.org/10.48084/etasr.2756

Fabbri, M. (2021). Property rights and prosocial behavior: Evidence from a land tenure reform implemented as randomized control-trial. Journal of Economic Behavior and Organization. https://doi.org/10.1016/j.jebo.2021.06.001

Fatima, S., Desouza, K. C., & Dawson, G. S. (2020). National strategic artificial intelligence plans: A multi-dimensional analysis. Economic Analysis and Policy. https://doi.org/10.1016/j.eap.2020.07.008

Goeb, J., Dillon, A., Lupi, F., & Tschirley, D. (2020). Pesticides: What you don’t know can hurt you. Journal of the Association of Environmental and Resource Economists. https://doi.org/10.1086/709782

Grimm, M., & Luck, N. (2020). Can Training Enhance Adoption, Knowledge and Perception of Organic Farming Practices? Evidence from a Randomized Experiment in Indonesia. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.3636629

Hananda, N., Kamul, A., Harito, C., Djuana, E., Elwirehardja, G. N., Pardamean, B., Gunawan, F. E., Budiman, A. S., Asrol, M., & Pasang, T. (2023). Solar drying in Indonesia and its development: A review and implementation. IOP Conference Series: Earth and Environmental Science. https://doi.org/10.1088/1755-1315/1169/1/012084

Haryanto, T., Wardana, W. W., & Basconcillo, J. A. Q. (2023). Does sending farmers back to school increase technical efficiency of maize production? Impact assessment of a farmer field school programme in Indonesia. Economic Research-Ekonomska Istrazivanja . https://doi.org/10.1080/1331677X.2023.2218469

Herdiansyah, H., Antriyandarti, E., Rosyada, A., Arista, N. I. D., Soesilo, T. E. B., & Ernawati, N. (2023). Evaluation of Conventional and Mechanization Methods towards Precision Agriculture in Indonesia. Sustainability (Switzerland). https://doi.org/10.3390/su15129592

Hübel (Anghel), E., Stan, M.-I., & Tasente, T. (2023). How respondents’ age influence perceptions of socio-economic issues in the context of sustainable local development. Eximia. https://doi.org/10.47577/eximia.v11i1.277

Iswan, M., Suryanata, M. G., Pane, D. H., Ibnutama, K., & Wijaya, R. F. (2022). Application of Artificial Intelligence In The Detection Of Plant Diseases (Clubroot). JURNAL TEKNOLOGI DAN OPEN SOURCE. https://doi.org/10.36378/jtos.v5i1.2372

Jarrahi, M. H. (2018). Artificial intelligence and the future of work: Human-AI symbiosis in organizational decision making. Business Horizons. https://doi.org/10.1016/j.bushor.2018.03.007

Linaza, M. T., Posada, J., Bund, J., Eisert, P., Quartulli, M., Döllner, J., Pagani, A., Olaizola, I. G., Barriguinha, A., Moysiadis, T., & Lucat, L. (2021). Data-driven artificial intelligence applications for sustainable precision agriculture. Agronomy. https://doi.org/10.3390/agronomy11061227

Liundi, N., Darma, A. W., Gunarso, R., & Warnars, H. L. H. S. (2019). Improving Rice Productivity in Indonesia with Artificial Intelligence. 2019 7th International Conference on Cyber and IT Service Management, CITSM 2019. https://doi.org/10.1109/CITSM47753.2019.8965385

Manish Yadav, & Gurjeet Singh. (2023). Environmental Sustainability With Artificial Intelligence. EPRA International Journal of Multidisciplinary Research (IJMR). https://doi.org/10.36713/epra13325

Mowla, M. N., Mowla, N., Shah, A. F. M. S., Rabie, K. M., & Shongwe, T. (2023). Internet of Things and Wireless Sensor Networks for Smart Agriculture Applications: A Survey. IEEE Access. https://doi.org/10.1109/ACCESS.2023.3346299

Muhtar, E. A., Abdillah, A., Widianingsih, I., & Adikancana, Q. M. (2023). Smart villages, rural development and community vulnerability in Indonesia: A bibliometric analysis. Cogent Social Sciences. https://doi.org/10.1080/23311886.2023.2219118

Nugroho, I., & Hakim, L. (2023). Artificial intelligence and socioeconomic perspective in Indonesia. Journal of Socioeconomics and Development. https://doi.org/10.31328/jsed.v6i2.5187

Nurmaini, S. (2021). The Artificial Intelligence Readiness for Pandemic Outbreak COVID-19: Case of Limitations and Challenges in Indonesia. Computer Engineering and Applications Journal. https://doi.org/10.18495/comengapp.v10i1.353

Nwokocha, G. (2020). Mainstreaming climate smart technology adaptation in Msinga’s farmers' everyday agricultural practices through university, smallholding farming community and government partnerships: the place and space for indigenous knowledge systems. July.

Oliveira, R. C. de, & Silva, R. D. de S. e. (2023). Artificial Intelligence in Agriculture: Benefits, Challenges, and Trends. In Applied Sciences (Switzerland). https://doi.org/10.3390/app13137405

Putra Adnyana, I. P. C., Astiti, L. G. S., Agustini, N., Hijriyah, & Hilmiati, N. (2021). Farmer’s perception on artificial insemination under the mandatory pregnant cow program (UPSUS SIWAB) in West Nusa Tenggara, Indonesia. E3S Web of Conferences. https://doi.org/10.1051/e3sconf/202130602029

Ramadhani, M. S., Junirianto, E., & Maria, E. (2022). System Monitoring and Controlling Agricultural Activities with Arduino-Based Internet of Things. TEPIAN. https://doi.org/10.51967/tepian.v3i4.1567

Ray, R., Agar, Z., Dutta, P., Ganguly, S., Sah, P., & Roy, D. (2021). MenGO: A Novel Cloud-Based Digital Healthcare Platform For Andrology Powered By Artificial Intelligence, Data Science & Analytics, Bio-Informatics And Blockchain. Biomedical Sciences Instrumentation. https://doi.org/10.34107/KSZV7781.10476

Salam, U., Lee, S., Fullerton, V., Yusuf, Y., Krantz, S., & Henstridge, M. (2018). Indonesia Case Study: Rapid Technological Change-Challenges and Opportunities Final Report. Pathways for Prosperity Commission.

Sarkar, M. R., Masud, S. R., Hossen, M. I., & Goh, M. (2022). A Comprehensive Study on the Emerging Effect of Artificial Intelligence in Agriculture Automation. 2022 IEEE 18th International Colloquium on Signal Processing and Applications, CSPA 2022 - Proceeding. https://doi.org/10.1109/CSPA55076.2022.9781883

Setiadi, D., Risma, P., Dewi, T., Kusumanto, R., & Oktarina, Y. (2020). Implementasi Neural Network Untuk Kendali Gerak Mobile Robot Pembasmi Hama. Journal of Applied Smart Electrical Network and Systems. https://doi.org/10.52158/jasens.v1i01.36

Sharma, N., Bohra, B., Pragya, N., Ciannella, R., Dobie, P., & Lehmann, S. (2016). Bioenergy from agroforestry can lead to improved food security, climate change, soil quality, and rural development. In Food and Energy Security. https://doi.org/10.1002/fes3.87

Sugandini, D., Effendi, M. I., Sugiarto, B., Kundarto, M., & Kawuryan, S. H. E. (2023). Resistance to Agricultural Commercialization with Lack of Marketing Digital Adoption in Indonesia’s Dieng Plateau. International Journal of Sustainable Development and Planning. https://doi.org/10.18280/ijsdp.180607

Taneja, A., Nair, G., Joshi, M., Sharma, S., Sharma, S., Jambrak, A. R., Roselló-Soto, E., Barba, F. J., Castagnini, J. M., Leksawasdi, N., & Phimolsiripol, Y. (2023). Artificial Intelligence: Implications for the Agri-Food Sector. In Agronomy. https://doi.org/10.3390/agronomy13051397

Tanggu Redu, S., Quartina PUDJIASTUTI, A., Sumarno, S., Sektörünün Doğu Java İl Ekonomisindeki Yeri, T., & Özet, E. (2020). Role of Agriculture Sector on the Economy of East Java Province, Indonesia (Input-Output Analysis). In Anatolian Journal of Economics and Business.

Veysel, A., Karadayi, T., & Makaritou, P. (2021). Investigating The Socio-Economic Consequences Of Artificial Intelligence: A Qualitative Research. In Journal of International Trade, Logistics and Law.

Vijayakumar, S., Kumar, R. M., Choudhary, A. K., & Murugesan, D. (2022). Artificial Intelligence (AI) and Its Application in Agriculture. Chronicle of Bioresource Management.

Yasinto, Y. (2023). Change of Agricultural Technology and Impacts on Farmer’s Relationship with Nature and Environment in Timor, Indonesia. International Journal of Social Science and Human Research. https://doi.org/10.47191/ijsshr/v6-i4-65


Refbacks

  • There are currently no refbacks.


_______________________________________________

 

Creative Commons License

Prosiding Seminar Nasional Pertanian
is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License

______________________________________________

PROSIDING TERINDEKS:

 

SEKRETARIAT PANITIA: