Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal Journal of Decision Support Systems and Multi-Criteria Decision Making (JODESMA)
Arie Qurania
Pakuan University

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
A Novel MPSI Weighting and Proximity Indexed Value Framework for Multi-Criteria Selection of Marketplace Logistics Partners Sufiatul Maryana; Arie Qurania; Agung Prajuhana Putra
Journal of Decision Support Systems and Multi-Criteria Decision Making Vol. 1 No. 1 (2026): November 2026
Publisher : Asosiasi Peneliti Informatika dan Komputer untuk Riset (PILAR)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.67449/jodesma.v1i1.4

Abstract

In facing the increasingly intense competition in the logistics industry, companies are often confronted with challenges in selecting the most appropriate logistics partner due to the many performance criteria that must be considered simultaneously. This study aims to evaluate and determine the best logistics partner using a Multi-Criteria Decision-Making approach through the integration of the MPSI method for criteria weighting and PIV for the alternative ranking process. The criteria used include Transit Time, On-Time Delivery, First-Attempt Success, Attempt Rate, and Package Volume, which are analyzed based on the performance data of each alternative. The weighting results indicate that Package Volume and Transit Time are the most dominant factors in the evaluation process. Based on the PIV method calculations, the ranking results were obtained, with NJ Logistics Partner occupying the first rank with a score of 0.46408, followed by TK Logistics Partner in second place with a score of 0.44014, and JT Logistics Partner in third place with a score of 0.39282. Sensitivity tests through various weight change scenarios showed that the ranking structure remained consistent, indicating that the model has a high level of stability and resilience to parameter variations. Overall, the proposed approach is able to produce decisions that are objective, measurable, and reliable as a basis for supporting strategic logistics partner selection.
Co-Authors Agung Prajuhana Putra Sufiatul Maryana