Klasifikasi Persediaan Barang Menggunakan Analisis Always Better Control (ABC) dan Prediksi Permintaan dengan Metode Monte Carlo

(Studi Kasus: Persediaan Obat Pada Apotek Mega Rizki Tahun 2016)

  • Ricca Noviani Mahasiswa Program Studi Statistika FMIPA Universitas Mulawarman
  • Yuki Novia Nasution Dosen Program Studi Statistika FMIPA Universitas Mulawarman
  • Nanda Arista Rizki Dosen Program Studi Statistika FMIPA Universitas Mulawarman

Abstract

ABC analysis is a method of inventory control to manage a small number of item but has a high utilization. Inventories are categorized into three classes A, B, and C. The objective of the research is to manage the inventories using ABC analysis, EOQ, ROP, and to provide an overview of the next-year demand of the drug items using Monte Carlo method. ABC analysis results show that out of 79 drug items, class A consists of 19 drug items with usage value 69,11%, class B consists of 19 drug items with usage value 20,29%, and class C consists of 41 drug items with usage value 10,60%. Based on economic order quantity method, minimum ordering quantity of drug are two items and maximum ordering quantity of drug are 96 items.Based on reorder point method, the minimum quantity of drug for reordering is zero item and the maximum quantity of drug for reordering are seven items. Monte Carlo method results show that Fludane Plus 60 ml has the minimum demand on January - Desember 2017 which is only one bottle a month and Actifed Cough Merah 60 ml has the maximum demand which is 78 - 81 bottles a month. Lapisiv 100 ml, Kamulvit B12 Sirup 120 ml, Fludane Plus 60 ml and Miconazole 2% has the highest accuration with the percentage of error 0% and Ikadryl DMP Sirup 100 mlhas the lowest accuration with the percentage of error 0,22%.

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Published
2017-12-21
How to Cite
NOVIANI, Ricca; NASUTION, Yuki Novia; RIZKI, Nanda Arista. Klasifikasi Persediaan Barang Menggunakan Analisis Always Better Control (ABC) dan Prediksi Permintaan dengan Metode Monte Carlo. EKSPONENSIAL, [S.l.], v. 8, n. 2, p. 103-110, dec. 2017. ISSN 2798-3455. Available at: <https://jurnal.fmipa.unmul.ac.id/index.php/exponensial/article/view/30>. Date accessed: 06 may 2024.
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Articles