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BukuIdentifikasi Dan Evaluasi Risiko Yang Terjadi Pada Anggota Rantai Pasok Kelapa Sawit Di Indonesia Dengan Metode Analytic Network Process
Bibliografi
Author: Immanuel, Nicholas ; Natalia, Christine (Advisor)
Topik: Anp; Oil Palm; Risk; Supply Chain
Bahasa: (ID )    
Penerbit: Program Studi Teknik Industri Fakultas Teknik Unika Atma Jaya     Tempat Terbit: Jakarta    Tahun Terbit: 2015    
Jenis: Theses - Undergraduate Thesis
Fulltext: Nicholas Immanuel’s Undergraduate Theses.pdf (7.24MB; 86 download)
Ketersediaan
  • Perpustakaan Pusat (Semanggi)
    • Nomor Panggil: FTI-1226
    • Non-tandon: tidak ada
    • Tandon: 1
 Lihat Detail Induk
Abstract
Oil Palm is one of the commodities whose role is very important to the national economy of Indonesia. Oil Palm plantation is the biggest contribution to earn the national income followed by rubber, coconut, and cocoa. The Oil Palm industry faces some global challenge and problems including the various risks involved in the oil palm supply chain. The purpose of this study is to identify and analyze a variety of disorders that arise at the highest risk of the oil palm supply chain in the critical unit, as well as the mitigation and suggestions in dealing with risks. The method which used to deciding and analyzing the highest risks in oil palm supply chain is Analytic Network Process (ANP). The actor of oil palm supply chain which identified as main farmers/plasma, traders, supplier,and oil palm industries. The identified risk of oil palm supply chain is quality, production, price, supply, transportation, and environment. The biggest risk faced by the farmers is the environment risk which pests and deseases become the biggest factor. The biggest risk faced by traders is the price which the fluctuation of price become the biggest factor. The biggest risk faced by supplier is the supply itself which the diversity of quality of supply become the biggest factor. The biggest risk faced by the oil palm industry is the production risk which low quality of raw materials is the most influence factor.
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