Optimization of Forecasting Method Selection in Overcoming Material Overstock and Stockout Problems in Instant Food Production (Case Study at PT. Mama Fuji Group)

Indah Tri Pertiwi; Tukhas Shilul Imaroh

doi:10.54408/jabter.v3i6.374

Authors

Indah Tri Pertiwi Universitas Mercu Buana Jakarta
Tukhas Shilul Imaroh Universitas Mercu Buana Jakarta

DOI:

https://doi.org/10.54408/jabter.v3i6.374

Keywords:

Overstock, Stockout, Forecasting, Time Series, Minitab 22

Abstract

PT Mama Fuji Group is a company that sells instant food through online platforms, such as Shopee, Lazada, Tokopedia, and Tiktok Shop. In 15 months in Q3 2022 - Q3 2023, PT Mama Fuji Group has a high fluctuation level, leading to a gap between production numbers and the actual demand. This problem causes several losses from the overstock or out-of-stock in finished goods warehouse. Hence, a company should prepare an effective production planning system, such as Forecasting. This research aimed to determine the most valid Forecasting using quantitative descriptive research methods with the Time Series method, such as Moving Average, SES (Single Exponential Smoothing), DES (Double Exponential Smoothing), or Holt’s Method, Linear Exponential Smoothing (Winter Method), and Trend Linear. Data is analyzed with Microsoft Excel and Minitab 22 software. Based on ABC analysis, products with code RNDG700, KB0002, KB0001, RNDGMINI, and DNDNG160 are the A class and five highest contributors, with 65,58% of total product value, and Winter Method becoming the best method, which had the most minor error presentation for the entire product item with MAPE value from each item is RNDG700 for 1,16%, KB0002 for 8%, KB0001 for 5%, RNDGMINI for 25% and DNDNG160 for 3,92%.

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