TY - GEN
T1 - Risk Analysis and Mitigation of Rice Supply Chain in Madura Island Using SCOR Model and AHP-TOPSIS Method
AU - Hozairi,
AU - Baskoro, Fajar
AU - Tukan, Marcus
AU - Alim, Syariful
AU - Ariyanto, Fathorrozi
AU - Tamam, Moh Badri
N1 - Publisher Copyright:
© 2024 IEEE.
PY - 2024
Y1 - 2024
N2 - This study aims to identify and formulate risk mitigation strategies for the rice supply chain in Madura Island using the SCOR model approach and the AHP-TOPSIS method. We use the SCOR model as a framework for the supply chain flow. We use AHP to assess the risks in the supply chain and prioritize risk mitigation strategies using TOPSIS. The results showed that the most significant risk was in the Source (S) category with a weight of 0.51, followed by the Make (M) risk of 0.22. In the Source category, the two most influential risks were supplying instability due to uncertain weather (S 5=0.50) and decreased raw material inventory (S1 =0.26). In the Make category, the risk of delays in rice production (M1=0.46) and weather uncertainty (M2=0.25) were the two most influential risks. In the Plan category, fluctuating demand (P1=0.49) and inaccurate production estimates (P2=0.24) are the two most influential risks, while in the Delivery category, scheduling problems (D1=0.45) and inaccurate delivery records (D2=0.23) are the two most influential risks. Based on TOPSIS calculations, three risk mitigation strategies identified as top priorities include maintaining stable supply and prices (A2=0.85), implementing information technology for supply chain monitoring (A12 = 0.74), and conducting accurate supply planning (M11 =0.55). This study makes a significant contribution to managing rice supply chain risks on Madura Island.
AB - This study aims to identify and formulate risk mitigation strategies for the rice supply chain in Madura Island using the SCOR model approach and the AHP-TOPSIS method. We use the SCOR model as a framework for the supply chain flow. We use AHP to assess the risks in the supply chain and prioritize risk mitigation strategies using TOPSIS. The results showed that the most significant risk was in the Source (S) category with a weight of 0.51, followed by the Make (M) risk of 0.22. In the Source category, the two most influential risks were supplying instability due to uncertain weather (S 5=0.50) and decreased raw material inventory (S1 =0.26). In the Make category, the risk of delays in rice production (M1=0.46) and weather uncertainty (M2=0.25) were the two most influential risks. In the Plan category, fluctuating demand (P1=0.49) and inaccurate production estimates (P2=0.24) are the two most influential risks, while in the Delivery category, scheduling problems (D1=0.45) and inaccurate delivery records (D2=0.23) are the two most influential risks. Based on TOPSIS calculations, three risk mitigation strategies identified as top priorities include maintaining stable supply and prices (A2=0.85), implementing information technology for supply chain monitoring (A12 = 0.74), and conducting accurate supply planning (M11 =0.55). This study makes a significant contribution to managing rice supply chain risks on Madura Island.
KW - AHP
KW - Mitigation
KW - Rice Supply Chain Risks
KW - SCOR
KW - TOPSIS
UR - http://www.scopus.com/inward/record.url?scp=105004579663&partnerID=8YFLogxK
U2 - 10.1109/ICIC64337.2024.10957703
DO - 10.1109/ICIC64337.2024.10957703
M3 - Conference contribution
AN - SCOPUS:105004579663
T3 - 2024 9th International Conference on Informatics and Computing, ICIC 2024
BT - 2024 9th International Conference on Informatics and Computing, ICIC 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 9th International Conference on Informatics and Computing, ICIC 2024
Y2 - 24 October 2024 through 25 October 2024
ER -