ANALISIS KINERJA RANTAI PASOK IKAN NILA PADA BANDAR SRIANDOYO DI KECAMATAN TUGUMULYO KABUPATEN MUSI RAWAS

  • Setiadi S
  • Nurmalina R
  • Suharno S
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Abstract

Abstract. Measurement of supply chain performance is a necessary as an approach inorder to optimize supply chain of tilapia fish in Musi Rawas Regency. The purpose ofthis research is to analyze the performance of the supply chain of tilapia fish, and theefficiency of supply chain performance of tilapia fish at Bandar Sriandoyo inTugumulyo District, Musi Rawas Regency. The method that employed to measure theperformance of supply chain of tilapia fish was by comparing the value of SCORmetric performance attribute on partner farmer and Bandar Sriandoyo with superiortarget value on benchmarking. Analysis of efficiency of supply chain performance oftilapia fish was employing Data Envelopment Analysis (DEA) method. The input andoutput variables were based on the performance attributes of SCOR metrics. The resultsof measuring the performance of the supply chain of tilapia fish on the partner farmersand Bandar Sriandoyo has generally achieved good performance compared to thebenchmark. Where some performance attributes had achieved the target of the superiorstatus that is the best performance achievement. While the attributes of deliveryperformance and conformity with the standard achived the target of the advantage(middle) status. The results of chain performance efficiency measurement showed that23 partner farmers (60%) had achieved technical efficiency and having 100%performance efficiency value. While 15 partner farmers (40%) had not reachedtechnical efficiency. Bandar Sriandoyo has achieved technical efficiency because it hasachived a 100% performance efficiency rate, which means that the input and outputfactors are running according to the target.

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APA

Setiadi, S., Nurmalina, R., & Suharno, S. (2018). ANALISIS KINERJA RANTAI PASOK IKAN NILA PADA BANDAR SRIANDOYO DI KECAMATAN TUGUMULYO KABUPATEN MUSI RAWAS. MIX: JURNAL ILMIAH MANAJEMEN, 8(1), 166. https://doi.org/10.22441/mix.2018.v8i1.010

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