Peran Artificial Intelligence (AI) dalam Pengembangan Circular Bioeconomy Berbasis Bioproses
Keywords:
Bioekonomy Circular, Artificial Intelligence, Rekayasa Bioproses, Anaerobic Digestion, Industry BerkelanjutanAbstract
Perkembangan circular bioekonomi adalah salah satu strategi penting dalam mendukung pembangunan industri berkelanjutan melalui pemanfaatan biomassa dan limbah organik secara efisien, sekaligus menjawab tantangan pengelolaan limbah, kebutuhan energi terbarukan, dan pengurangan emisi karbon. Teknologi Artificial Intelegence (AI) di terapkan untuk meningkatkan efisiensi konversi biologis pada proses fermentasi anaerobic digestion (AD), dan pengelolaan biomassa. Artikel review ini bertujuan mengkaji peran AI dalam pengembangan circular bioekonomi berbasis bioproses. Metode yang digunakan berupa studi literatur terhadap artikel ilmiah yang membahas penerapan AI pada sistem bioproses, bioenergi, dan pengelolaan limbah biologis. Hasil kajian menunjukkan bahwa integrasi AI khususnya melalui machine learning, artificial neural network, dan sistem monitoring cerdas, mampu meningkatkan optimasi parameter proses, stabilitas reaktor, akurasi prediksi kinerja, serta efisiensi pemanfaatan sumber daya biologis. AI juga berkontribusi dalam mendukung waste valorization, pengurangan konsumsi energi, dan peningkatan produksi bioenergi. Kendala yang dihadapi adalah keterbatasan dan kualitas, biaya integrasi teknologi, dan kompleksitas sistem biologis. AI berpotensi menjadi teknologi kunci dalam mempercepat transformasi bioindustri menuju circular bioekonomi yang lebih efisien, adaptif, dan berkelanjutan
Downloads
References
[1] A. J. de Lucas López, C. L. Vera, and Á. J. Álvarez Miguel, “Artificial intelligence as a catalyst for the circular economy: a mixed-methods analysis of sustainable production ecosystems (2023–2024),” International Entrepreneurship and Management Journal, vol. 22, no. 2, Jun. 2026, doi: 10.1007/s11365-026-01176-y.
[2] M. Shah, M. Wever, and M. Espig, “A Framework for Assessing the Potential of Artificial Intelligence in the Circular Bioekonomi,” Sustainability (Switzerland), vol. 17, no. 8, Apr. 2025, doi: 10.3390/su17083535.
[3] D. B. Olawade et al., “Smart waste management: A paradigm shift enabled by artificial intelligence,” Jun. 01, 2024, Elsevier B.V. doi: 10.1016/j.wmb.2024.05.001.
[4] T. Huntington, N. R. Baral, M. Yang, E. Sundstrom, and C. D. Scown, “Machine learning for surrogate process models of bioproduction pathways,” Bioresour. Technol., vol. 370, Feb. 2023, doi: 10.1016/j.biortech.2022.128528.
[5] A. Madanaguli, D. Sjödin, V. Parida, and P. Mikalef, “Artificial intelligence capabilities for circular business models: Research synthesis and future agenda,” Technol. Forecast. Soc. Change, vol. 200, Mar. 2024, doi: 10.1016/j.techfore.2023.123189.
[6] T. H. Tsui, M. C. M. van Loosdrecht, Y. Dai, and Y. W. Tong, “Machine learning and circular bioekonomi: Building new resource efficiency from diverse waste streams,” Bioresour. Technol., vol. 369, p. 128445, Feb. 2023, doi: 10.1016/J.BIORTECH.2022.128445.
[7] E. Alepu Odey, K. Wang, Z. Li, and R. Gao, “Influence of organik loading rates on the production of methane from anaerobic digestion of sewage concentrate,” Energy and Environment, vol. 29, no. 7, pp. 1130–1141, Nov. 2018, doi: 10.1177/0958305X18769860.
[8] N. Kythreotou, G. Florides, and S. A. Tassou, “A review of simple to scientific models for anaerobic digestion,” 2014, Elsevier Ltd. doi: 10.1016/j.renene.2014.05.055.
[9] F. Tufaner, K. Dalkılıç, and A. Uğurlu, “Artificial intelligence-based modeling of biogas production in a combined microbial electrolysis cell-anaerobic digestion system using artificial neural networks and adaptive neuro-fuzzy inference system,” Environmental Science and Pollution Research, vol. 32, no. 20, pp. 12524–12546, Apr. 2025, doi: 10.1007/s11356-025-36467-4.
[10] S. Ö. Cinar, S. Cinar, and K. Kuchta, “Machine Learning Algorithms for Temperature Management in the Anaerobic Digestion Process,” Fermentation, vol. 8, no. 2, Feb. 2022, doi: 10.3390/fermentation8020065.
[11] G. Rybak et al., “Algorithms for Optimizing Energy Consumption for Fermentation Processes in Biogas Production,” Energies (Basel)., vol. 16, no. 24, Dec. 2023, doi: 10.3390/en16247972.
[12] H. Rutland, J. You, H. Liu, L. Bull, and D. Reynolds, “A Systematic Review of Machine-Learning Solutions in Anaerobic Digestion,” Dec. 01, 2023, Multidisciplinary Digital Publishing Institute (MDPI). doi: 10.3390/bioengineering10121410.
[13] A. Khanal, S. Giri, and P. Mainali, “The Practices of At-Source Segregation of Household Solid Waste by the Youths in Nepal,” J. Environ. Public Health, vol. 2023, pp. 1–6, Feb. 2023, doi: 10.1155/2023/5044295.
[14] M. Shah, M. Wever, and M. Espig, “A Framework for Assessing the Potential of Artificial Intelligence in the Circular Bioekonomi,” Sustainability (Switzerland), vol. 17, no. 8, Apr. 2025, doi: 10.3390/su17083535.
[15] N. Prabhu and S. Kadry, “Intelligent waste valorization: AI, bioprocessing, and thermochemical conversion for circular bioekonomi transitions,” Cleaner Waste Systems, vol. 14, Jun. 2026, doi: 10.1016/j.clwas.2026.100509.
