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All Journal Populer: Jurnal Penelitian Mahasiswa
Hizrio Corenlius Kusuma
Universitas 17 Agustus 1945 Surabaya
Humanities Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Social Sciences Other

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Analisis Pengendalian Persediaan Bahan Baku Perishable pada Sistem Dual Channel Supply Chain Menggunakan Metode Periodic Review System : Studi Kasus: Rumah Makan Mie Paus Hizrio Corenlius Kusuma; Hilyatun Nuha
Populer: Jurnal Penelitian Mahasiswa Vol. 5 No. 2 (2026): Juni: Populer: Jurnal Penelitian Mahasiswa
Publisher : Universitas Maritim AMNI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58192/populer.v5i2.4552

Abstract

Mie Paus Restaurant operates through both offline and online sales channels, creating fluctuating demand patterns that affect perishable raw material inventory requirements. Demand uncertainty increases the risk of stockouts and overstock situations, which may disrupt production activities. This study aims to analyze perishable inventory control and propose an inventory policy using the Periodic Review System. The data include product demand from July–December 2025, Bill of Material (BOM), lead time, and inventory records. The research stages consist of demand aggregation from offline and online channels, demand forecasting, BOM-based material requirement planning, and inventory parameter calculations. The results indicate that the Moving Average (MA-3) method is the most accurate forecasting model with MAD of 80.11, MSE of 11,990.11, and MAPE of 4.35%, generating a January 2026 demand forecast of 5,684 portions. The proposed Periodic Review System results in a 7-day review period, a 95% service level, safety stocks of 42 eggs, 1 kg of chicken skin, 11 bundles of mustard greens, and 520 portions of noodle dough. The target inventory levels are 167 eggs, 2 kg of chicken skin, 20 bundles of mustard greens, and 1,873 portions of noodle dough. The proposed approach provides a more structured and data-driven inventory control system compared with the company’s current practice.
Co-Authors Hilyatun Nuha