Efektivitas Penerapan Sistem Artificial Intelligence Fuzzy Logic Terhadap Peningkatan Pendapatan Petani Biji Kakao
DOI:
https://doi.org/10.33884/psnistek.v7i1.10728Kata Kunci:
Artificial Intelligence, biji kakao, Fuzzy Logic, sistem rekomendasi harga, kebijakanAbstrak
The distribution chain of plantation commodities continues to encounter persistent structural challenges, particularly effecting the bargaining position of farmers, who remain at a disadvantage when negotiating with intermediaries. This issue is notably experienced by cocoa bean farmers in Southeast Sulawesi. In response to this, the present study examines the development and implementation of an Artificial Intelligence (AI)-based information system utilizing fuzzy logic algorithms to predict and recommend cocoa bean selling prices in real time. The system also visualizes real time market price fluctuations through dynamic graphs. Designed not only to enhance farmers’ acces to timely and accurate market information, the system also aims to improve their bargaining power and contribute to more transaparent and equitable pricing practice. Furthermore, the system serves as decision support tool for local governments by providing reliable, data driven insights for policy formulation. Research used SWOT approach and was analyzed descriptively qualitatively. The prediction system achieved an accuracy rate of 92%, determined by comparing product price values calsulated using fuzzy logic algorithms with actual market prices. Price prediction information system is implemented as a mobile application, making it accesible to farmers, buyers and relevant government agencies. This innovation represents a strategic digital intervention to promote price transparency, enhance farmer welfare and support evidence based policymaking in the agricultural sector.
Referensi
Agapitova, L., Butorina, G., Larionova, N., & Medvedeva, L. (2023). Digital transformation of the agro-industrial complex as a transition to highly efficient production. E3S Web of Conferences, 390. https://doi.org/10.1051/e3sconf/202339003023
Analysis, R. L. (2024). Trace-2-Place. April.
Ankuyi, F., Tham-Agyekum, E. K., Bakang, J.-E. A., Quayson, N., Okantah, D., Hope, T., Osei-Nyarko, J., & Wesley, R. R. (2023). Local Voices for CocoaProduction: Experiences of Ghanaian Cocoa Farmers on Community Radio. International Journal on Food, Agriculture and Natural Resources, 4(1), 34–43. https://doi.org/10.46676/ijfanres.v4i1.126
Araujo, S. O., Peres, R. S., Filipe, L., MantaCosta, A., Lidon, F., Ramalho, J. C., & Barata, J. (2023). Intelligent DataDriven Decision Support for Agricultural Systems-ID3SAS. IEEE Access, 11, 115798–115815. https://doi.org/10.1109/ACCESS.2023.3324813
Asia, A. (n.d.). Regional United Nations Group for Europe and Central Asia on Digital Transformation Supporting Digital Transformation in Europe and Central Asia: Accelerating Achievement of Sustainable Development Goals Regional United Nations Group for Europe and Centra. March 2021.
Ben-Shahar, O. (2009). A bargaining power theory of default rules. Columbia Law Review, 109(2), 396–430.
Chen, J., Hou, H., Liao, Z., & Wang, L. (2024). Digital Environment, Digital Literacy, and Farmers’ Entrepreneurial Behavior: A Discussion on Bridging the Digital Divide. Sustainability (Switzerland), 16(23), 1–18. https://doi.org/10.3390/su162310220
Cui, X., Yang, J., Fan, Z., & Wang, Y. (2025). Does the Improvement of Farmers Digital Literacy Restrain Their Opportunistic Behavior When They Choose Pest Control Methods in Certified Agro-Products ? 1–28.
Díez-González, J., Verde, P., FerreroGuillén, R., Álvarez, R., & Pérez, H. (2020). Hybrid memetic algorithm for the node location problem in local positioning systems. Sensors (Switzerland), 20(19), 1–26. https://doi.org/10.3390/s20195475
Economics, A., & Library, D. (n.d.). This document is discoverable and free to researchers across the globe due to the work of AgEcon Search . Help ensure our sustainability . Agricultural Price Forecasting Using Neural Network Model : An.
Future Today Strategy Group. (2025). 2025 Tech Trends Report. 1–979. https://futuretodayinstitute.com/reports/
Goñas, M., Rojas-Briceño, N. B., Gómez Fernández, D., Iliquín Trigoso, D., Atalaya Marin, N., Bravo, V. C., DíazValderrama, J. R., Maicelo-Quintana, J. L., & Oliva-Cruz, M. (2024). Economic Profitability of Carbon Sequestration of Fine-Aroma Cacao Agroforestry Systems in Amazonas, Peru. Forests, 15(3), 1–17. https://doi.org/10.3390/f15030500
Gumber, P. (2021). Role Of Community Radios In Rural Development: A Quantitative Investigation. 20(6), 5038–5045. https://doi.org/10.17051/ilkonline.2021.06.493
Hegde, G., Hulipalled, V. R., & Simha, J. B. (2023). Data driven algorithm selection to predict agriculture commodities price. International Journal of Electrical and Computer Engineering, 13(4), 4671–4682. https://doi.org/10.11591/ijece.v13i4.pp4671-4682
Kanellos, N., Karountzos, P., Giannakopoulos, N. T., Terzi, M. C., & Sakas, D. P. (2024). Digital Marketing
Strategies and Profitability in the Agri-Food Industry: Resource Efficiency and Value Chains. Sustainability (Switzerland), 16(14). https://doi.org/10.3390/su16145889
Kumar, P. B. P., Rao, K. T., Bharathalakshmi, M., & Rambabu, P. (2023). Digital marketing of agriculture inputs- An institutional success story. International Journal of AgriculturalSciences, 19(2), 737–739. https://doi.org/10.15740/has/ijas/19.2/737-739
Ladhar, R., Sharma, S., Tangirala, S., Gupta, N., Azeem, A., Jain, A., Katakam, B. C., Bommakanti, A., Sankaraiah, C., Piridi, H. P., Yadav, K., Vittalrao, K., Rahman, M., Chutani, R., Shah, R., Katepallewar, R., Chakraborty, D., & Seth, A. (2023). AI-based Market Intelligence Systems for Farmer Collectives: A Case Study from India. ACM Journal on Computing and Sustainable Societies, 1(1), 1–32. https://doi.org/10.1145/3609262
Liu, H., Chen, Z., Wen, S., Zhang, J., & Xia, X. (2025). Impact of Digital Literacy on Farmers’ Adoption Behaviors of Green Production Technologies.Agriculture (Switzerland), 15(3).
https://doi.org/10.3390/agriculture15030303
Lutsiі, O., & Helevei, O. (2023). Formation of Components of the Marketing Information System for Agricultural Products Using Big Data Methods. Oblik i Finansi, 3(3(101)), 145–151. https://doi.org/10.33146/2307-9878-2023-3(101)-145-151
Maina, F., Mburu, J., & Nyang’anga, H. (2024). Drivers of extent of commercialization of potato farming through digital marketing platforms in Nakuru County, Kenya. Frontiers in Sustainable Food Systems, 8(February). https://doi.org/10.3389/fsufs.2024.1307978
Maru, A., Berne, D., Beer, J. De, Ballantyne, P., Pesce, V., Kalyesubula, S., Fourie, N., Addison, C., Collett, A., Chaves, J., Maru, A., Berne, D., De Beer, J., Ballantyne, P., Pesce, V., Kalyesubula, S., Fourie, N., Addison, C., Collett, A., & Chaves, J. (2018). Digital and Data-Driven Agriculture: Harnessing the Power of Data for Smallholders. F1000Research 2018 7:525, 7, 525. https://f1000research.com/documents/7-525
Maslej, N. (2025). Artificial Intelligence Index Report Introduction to the AI Index Report 2025 GP-003. Artificial Intelligence Index Report 2025, 1–456.
Ning, K., & Rubin, J. (2021). Data driven artificial intelligence techniques in renewable energy system. 1999. https://dspace.mit.edu/handle/1721.1/132891
Novianti, E. (2023). Akselerasi Literasi Digital Sebagai Pengembangan Komunikasi Pariwisata Pada Kawasan Geopark Bandung. Dharmakarya, 12(2), 290. https://doi.org/10.24198/dharmakarya.v12i2.43327
Ojo, A. K., & Ogundare, M. A. (2018). Offline Accessible System for Agricultural ECommerce Using Unstructured Supplementary Services Data
Application. International Journal of Computer Science and Telecommunications, 9(6), 5–11.
Pamungkas, R. J., Haryanto, H., Astuti, S., Astuti, E. Z., & Rahayu, Y. (2020). Rekomendasi Penentuan Harga Jual Untuk Warangka Keris Menggunakan
Logika Fuzzy Mamdani. Jurnal Ilmu Komputer, 13(1). https://doi.org/10.24843/jik.2020.v13.i01.p06
Papadakis, I. E., Ladikou, E. V., Oikonomou, A., Chatzistathis, T., & Chatziperou, G. (2023). Exploring the Impact of Potassium on Growth, Photosynthetic Performance, and Nutritional Status of Lemon Trees (cv. Adamopoulou) Grafted onto Sour Orange and Volkamer Lemon Rootstocks. Sustainability (Switzerland), 15(22). https://doi.org/10.3390/su152215858
Pavithra, S., Gracy, C. P., Saxena, R., & Patil, G. G. (2018). Innovations in agricultural marketing: a case study of e-tendering system in Karnataka, India.
Agricultural Economics Research Review, 31(1). https://doi.org/10.5958/0974-0279.2018.00005.8
Puspitafuri C; Kasmawati. (2025). INTEGRASI ARTIFICIAL INTELLIGENCE UNTUK PREDIKSI HARGA BIJI KAKAO DAN ECOMMERCE DALAM MENINGKATKAN NILAI JUAL PETANI. Jurnal Bisnis Digital, 1(1), 44–54
Rahmadani, E., & Elinur, E. (2024). Digital Marketing Strategies in Increasing the Competitiveness of Agricultural Products in the Digital Economy Era. Global International Journal of Innovative Research, 2(9), 2152–2164. https://doi.org/10.59613/global.v2i9.307
Saberi, S., Kouhizadeh, M., Sarkis, J., & Shen, L. (2019). Blockchain technology and its relationships to sustainable supply chain management. International Journal of Production Research, 57(7). https://doi.org/10.1080/00207543.2018.1533261
Sakib, N., Bakibillah, A. S. M., Susilawati, S., Kamal, M. A. S., & Yamada, K. (2024). Eco-Friendly Smart Car Parking Management System with Enhanced Sustainability. Sustainability (Switzerland) , 16(10), 1–14. https://doi.org/10.3390/su16104145
Sarabia, N., & Peris, J. (2024). Emergence and Development of Transformative Capacities for the Sustainability of the Agri-Food System: The Process in Valdivia, Chile. Sustainability (Switzerland) , 16(11). https://doi.org/10.3390/su16114849
Sari, M., Saediman, H., & Limi, M. A. (2019). Analisis Perbedaan Produksi dan Pendapatan Usahatani Kakao Petani Anggota dan Non Anggota LEM (Lembaga Ekonomi Masyarakat) sejahtera di Kecamatan Besulutu Kabupaten Konawe. Jurnal Ilmiah Membangun Desa Dan Pertanian, 4(5). https://doi.org/10.33772/jimdp.v4i5.8119
Snyder, L. V., & Shen, Z. J. M. (2019). Fundamentals of supply chain theory, second edition. In Fundamentals of Supply Chain Theory. https://doi.org/10.1002/9781119584445
Surdu, A., & Sitepu, F. M. (2021). Environmental Sustainability of the Digitalized Food Supply Chains in Indonesia.
Teresa, M., Lirag, B., Isabel, R., & Ramirez, S. (2024). Market Landscape and Digital Presence of Cacao-based Products in Bicol Region , Philippines. 24(11), 178–189.
Utoyo, D. B. (2025). Empowering Rural Communities through Digital Literacy : An Empirical Study of Former Women Migrant Workers in Panjer Village , Kebumen - Indonesia(Issue Icispe 2024). Atlantis Press SARL. https://doi.org/10.2991/978-2-38476-436-5
Vahdanjoo, M., Sørensen, C. G., & Nørremark, M. (2025). Digital transformation of the agri-food system. Current Opinion in Food Science, 63, 101287. https://doi.org/10.1016/j.cofs.2025.101287
Wajdah, R. R., & Nurmalina, R. (2024). Transformation Digital Supply Chain Management in Agriculture: A Systematic Literature Review. Prosiding Seminar Nasional Forum Manajemen Indonesia - e-ISSN 3026-4499, 2(February), 908–922. https://doi.org/10.47747/snfmi.v2i1.2076
Wang, Y., Weng, F., & Huo, X. (2023). Can Digital Finance Promote Professional Farmers’ Income Growth in China?— An Examination Based on the Perspective of Income Structure. Agriculture (Switzerland), 13(5). https://doi.org/10.3390/agriculture13051103
Zulkifli, Hakim, A., Soekotjo, E., Yusuf, Samdin, Zaid, S., Saefuddin, D. T., Madjid, R., & Rommy, N. (2025). Digital Strategy, Digital Leadership, Organizational Agility, and Digital Transformation for Agricultural Business Sustainability: A Human Resource Management Review. Journal of Global Innovations in Agricultural Sciences, 13(1), 273–283. https://doi.org/10.22194/JGIAS/25.1526
##submission.downloads##
Diterbitkan
Cara Mengutip
Terbitan
Bagian
Lisensi
Hak Cipta (c) 2025 Prosiding
Artikel ini berlisensi Creative Commons Attribution 4.0 International License.
