Published at : 29 May 2026
Volume : IJtech
Vol 17, No 3 (2026)
DOI : https://doi.org/10.14716/ijtech.v17i3.8148
| Marimin Marimin | Department of Agro-industrial Technology, Faculty of Agricultural Technology, IPB University, Bogor, Indonesia |
| Moh Yani | Department of Agro-industrial Technology, Faculty of Agricultural Technology, IPB University, Bogor, Indonesia |
| Machfud Machfud | Department of Agro-industrial Technology, Faculty of Agricultural Technology, IPB University, Bogor, Indonesia |
| Hartrisari Hardjomijojo | Department of Agro-industrial Technology, Faculty of Agricultural Technology, IPB University, Bogor, Indonesia |
| Muhammad Asrol | Industrial Engineering Department, BINUS Graduate Program – Master of Industrial Engineering, Bina Nusan- tara University, Jakarta, 11480, Indonesia |
| Elisa Anggraini | Department of Agro-industrial Technology, Faculty of Agricultural Technology, IPB University, Bogor, Indonesia |
| Irman Hermadi | School of Data Science, Mathematics, and Informatics, IPB University, Bogor, 16680, Indonesia |
| Rohayati Rohayati | Research Center for Composites and Biomaterials, Nanotechnology and Material Research Organisation, The National Research and Innovation Agency (BRIN), South Tangerang 15314, Indonesia |
| Fatata Aizza Rosyada | Logistics and Agro-Maritime Graduate Program, IPB University, Bogor, 16680, Indonesia |
| Ida Rosyidah | Logistics and Agro-Maritime Graduate Program, IPB University, Bogor, 16680, Indonesia |
| Sri Martini | Department of Agro-industrial Technology, Faculty of Agricultural Technology, IPB University, Bogor, Indonesia |
Indonesia’s sugarcane agroindustry plays a crucial role in gross domestic product, yet it faces threats to supply chain sustainability. Empirical studies on selected sugarcane agroindustries are needed to analyse and improve sustainability performance. This study aims to develop a strategy for enhancing the supply chain sustainability performance of the sugarcane agroindustry through performance measurement and empirical case studies. This study employs the fuzzy inference system method, multidimensional scaling, and an adaptive neuro-fuzzy inference system to assess supply chain sustainability performance. This study focuses on economic, social, environmental, and resource sustainability dimensions using 29 indicators. These indicators are subsequently aggregated to evaluate the supply chain’s overall sustainability performance. Empirical studies were conducted on two sugarcane agroindustry supply chains to assess the effectiveness of the supply chain and develop strategies for enhancing performance. The sustainability performance of sugar factories by 2023 is almost sustainable and medium sustainable. This study successfully developed lessons learned for sustainability improvement strategies tailored to each agroindustry based on key indicators. Agro-industries are expected to enhance their supply chain sustainability performance and ensure long-term economic, social, and environmental benefits by implementing these strategies. The following lessons were extracted: operational implementation and indicator adjustment, data quality and infrastructure, data pre-processing, and interpretation for managerial decision-making. The methodology for analysing performance and improvement strategies can be implemented to improve the future sustainability performance of the sugarcane agroindustry supply chain.
Agroindustry; Sugarcane; Strategy; Supply chain; Sustainability
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