PENGURANGAN NILAI INVENTORY LEVEL AKIBAT FORECAST DEMAND DAN FORECAST STOCK YANG DIPENGARUHI PANDEMI COVID-19 PADA RANTAI PASOK RITEL PRODUK FASHION FOOTWEAR MENGGUNAKAN METODE LONG SHORT TERM MEMORY PADA PT XYZ

Farah Rahmatika, . (2022) PENGURANGAN NILAI INVENTORY LEVEL AKIBAT FORECAST DEMAND DAN FORECAST STOCK YANG DIPENGARUHI PANDEMI COVID-19 PADA RANTAI PASOK RITEL PRODUK FASHION FOOTWEAR MENGGUNAKAN METODE LONG SHORT TERM MEMORY PADA PT XYZ. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.

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Abstract

PT. XYZ is a retail company for clothing, food and household needs in Indonesia. However, with the COVID-19 pandemic in Indonesia in early 2020, the retail industry, including PT. XYZ has an influence in the number of sales so that the forecast results are wrong and succeeded in making the inventory level at PT XYZ rise above the predetermined standard. The purpose of this study is to determine the optimal amount in forecasting from sales data and existing shoe product inventory so that it can improve the quality of PT XYZ's inventory level by using the LSTM method and the accuracy test is seen from the RSME value. There are 3 scenarios X and Y, the first X=actual stock, planned stock and Y=actual sales, the second X=actual stock, moving average (n, n-1) and Y= actual sales, the last X=Stock Plan, Sales and Y = actual stock which produces the best RSME value in scenario 3 with an accuracy rate of 90.66%. With the smallest RMSE value, scenario 3 can prove that the prediction results for actual stock can reduce inventory levels for excess IL values and increase inventory levels for less than IL standard.

Item Type: Thesis (Skripsi)
Additional Information: [No. Panggil: 1810312054], [Pembimbing: Yulizar Widiatama], [Penguji 1: Reda Rizal], [Penguji 2: Nurfajriah]
Uncontrolled Keywords: Forecast demand, Forecast Stock, LSTM, Deep Learning, Inventory
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
T Technology > T Technology (General)
T Technology > TS Manufactures
Divisions: Fakultas Teknik > Program Studi Teknik Industri (S1)
Depositing User: Farah Rahmatika
Date Deposited: 02 Mar 2022 04:43
Last Modified: 02 Mar 2022 04:43
URI: http://repository.upnvj.ac.id/id/eprint/16635

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