MODEL ABC MULTI-CRITERIA INVENTORY CLASSIFICATION (MCIC) MENGGUNAKAN PEMROGRAMAN LINEAR PADA PRODUK KIMIA
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Abstract
In order to maintain their inventory efficiently, enterprises need to prioritize inventory policies considering multiple criteria. A Multi Criteria Inventory Classification (MCIC) is one of the most effective techniques widely used to classify inventory. In this paper, multiple criteria (annual value, lead time, cost per unit) are considered on ABC inventory classification. The aim of this study is classify products considering those multiple criteria. Multiple criteria ABC Classifications methodology developed by Ramanathan-Model and Ng-Model are used and compared with traditional method. Data are collected from annual chemical product transaction on PT XYZ during 2018. In this paper, linear programming method is used to solve ABC MCIC Model. The result of this study show that 12 items (14%) are identified as Class A, 26 items (30%) as class B and the remaining 48 items (56%) as C Class. In our conclution, we propose inventory policies based on the result of the ABC Models.
Keywords: ABC Model; MCIC; Traditional Model; Ramanathan-Model; Ng-Model; Linear Programming; Chemical Product.
Abstrak
Dalam mengelola persediaan secara efisien, perusahaan perlu menentukan prioritas pengelolaan persediaan dengan mempertimbangkan beberapa kriteria. Klasifikasi ABC Multi Kriteria (MCIC) merupakan model klasifikasi persediaan barang yang umum digunakan oleh perusahaan dalam mengelola persediaan dalam jumlah besar. Penelitian ini menggunakan multi kriteria berupa nilai total produk, lead time dan biaya per unit. Tujuan penelitian adalah mengelompokan jenis/kelas barang sesuai dengan tingkat kepentingan dengan mempertimbangkan multi kriteria. Metode Multi kriteria yang telah dikembangkan oleh Ramanathan-Model dan Ng-Model dibandingkan dengan hasil klasifikasi Single criteria ABC (Traditional model). Data yang digunakan adalah data tahunan transaksi produk kimia PT XYZ di tahun 2018. Penyelesaian model ABC multi kriteria (MCIC) dengan pemrograman linear. Terdapat 86 items produk kimia yang diklasifikasikan dengan hasil klasifikasi A sejumlah 12 item (14%), B sejumlah 26 item (30%) dan item C sejumlah 48 item (56%). Pada penelitan ini juga disampaikan kebijakan inventory masing-masing kelas berdasarkan hasil klasifikasi ABC model yang telah dilakukan.
Kata Kunci: Model ABC; MCIC; Model tradisional; Model Ramanathan; Model Ng; Pemrograman Linear; Produk kimia.
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