PRIORITIZING SUPPLIER SELECTION TO REDUCE SCOPE 3 EMISSIONS USING THE ANALYTIC HIERARCHY PROCESS (AHP)

Silvia Anggraini (Institut Teknologi Bandung)
Yudo Anggoro (Institut Teknologi Bandung)

Multidiciplinary Output Research for Actual and International Issue (Morfai Journal)
Vol. 6 No. 2 (2026): Multidiciplinary Output Research For Actual and International Issue

The research addresses problems in supplier selection for collaboration to reduce Scope 3 emissions at PT Sejahtera Indonesia (PTSI). It is driven by the company's need to achieve net-zero emissions by 2050, in line with the global target. Reducing Scope 3 emissions is important because it covers most of the total emissions. However, the company faces difficulties in reducing emissions because of a large number of suppliers. The company can’t collaborate with all suppliers due to limited time and resources. Therefore, the company must prioritize suppliers that will have a significant impact on collaboration to reduce Scope 3 emissions. This research will use qualitative methods through literature review and FGD, and quantitative methods through a pairwise comparisons questionnaire for AHP. Previous journals have used various criteria for supplier selection. These criteria are then filtered based on their suitability for the research topic, resulting in six criteria that will be proposed and discussed in the FGD. FGD is conducted with four experts to determine the final criteria to be used in the AHP method. AHP is used as a data analysis method to prioritize criteria and alternatives based on the determined criteria. The final criteria are green image, environmental management system, environmental commitment, and carbon emissions. In the alternatives result, Supplier B is the most priority supplier, with a weight of 56.96%. Supplier B has the highest score and is showing strong performance across all criteria. Followed by Supplier E, Supplier A, Supplier D, and Supplier C. These results provide solutions for PTSI, enabling collaboration with suppliers with the highest potential for emissions reduction, considering several criteria.