ANALISIS PENGUKURAN KINERJA RANTAI PASOK PRODUK PERTAMAX MENGGUNAKAN MODEL SCOR (STUDI KASUS: PT PERTAMINA PATRA NIAGA FUEL TERMINAL JAMBI)

Abstract

PT Pertamina Patra Niaga Fuel Terminal Jambi has a great responsibility in fulfilling the supply of fuel oil needs, especially pertamax products for Public Fuel Filling Stations (SPBU). Jambi Fuel Terminal is located on Jalan Raden Pamuk No. 02 Kasang, East Jambi District, Jambi Province 36141. The Jambi Fuel Terminal has an area of about 92,700 M2 (10 Ha) and was built and operated in 1959. In the context of the supply chain, this study involves two actors, namely, the Jambi Fuel Terminal as a distributor and the petrol station as a retailer. The supply chain cycle view is at the Replenishment cycle level. From the preliminary study, it is known that there are several problems that cause the performance of FT Jambi's supply chain to be less than optimal, namely the demand for pertamax products that continues to increase at petrol stations, which causes the total distribution to be higher than the Actual Receipt received from IT Tanjung Uban and results in the inventory in the storage tank approaching the dead stock limit, as well as exceeding the coverage day limit of the Jambi Fuel Terminal. When the actual receipt is lower than the distribution, it results in the inventory in the storage tank almost approaching the dead stock limit. The model used is the Supply Chain Operational Reference (SCOR) which focuses on designing performance indicators for the supply chain process. This study conducted 3 stages of mapping which is the scope of the SCOR model. The process of designing performance indicators is carried out by distributing questionnaires involving 3 respondents and then processed using the Analytical Hierarchy Process (AHP) method assisted by the Expert Choice software tool related to the weighting of each criterion. This study has 10 Key Performance Indicators (KPIs), of which 9 KPIs are from the company and 1 KPI is from existing research references. From the results of data processing in stage 1, the deliver factor is the most dominant with a weight of 0.4584 and the return factor is the lowest with a weight of 0.032. As a result of stage 2 processing, the responsivity factor in the return gets the highest weight of 0.686 and the flexibility factor in the return is the lowest with a weight of 0.314. The results of stage 3 processing showed that the highest weight value was obtained in KPI-3 Storage stock accuracy with a weight of 0.142 and the lowest weight value was obtained in KPI 10 - Complaint response performance with a weight of 0.066.