PREDIKSI PERSEDIAAN SPAREPART MOTOR LISTRIK BERDASARKAN KLASIFIKASI ALWAYS BETTER CONTROL (ABC) MENGGUNAKAN METODE RECURRENT NEURAL NETWORK (RNN) PADA PT XYZ

Hisyam Raka Prasnantyo, . (2024) PREDIKSI PERSEDIAAN SPAREPART MOTOR LISTRIK BERDASARKAN KLASIFIKASI ALWAYS BETTER CONTROL (ABC) MENGGUNAKAN METODE RECURRENT NEURAL NETWORK (RNN) PADA PT XYZ. Skripsi thesis, Universitas Pembangunan Nasional Veteran Jakarta.

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Abstract

PT XYZ is an automotive electric motorbike manufacturing company originating from Indonesia and located in West Java since 2022. PT In the production of this model of electric motorbike, PT XYZ experienced the problem of overstock of spare parts that make up electric motorbikes. One of the inventory forecasting models used to overcome overstock is RNN (Recurrent Neural Network). The research results show a decrease in the total amount of stock for the next 2 months by 6.44%. The most accurate prediction data from the Recurrent Neural Network model uses an epoch of 25 with an RMSE value of 0.0191 or an accuracy level of 98.09%. Comparison of purchase costs before and after produces a difference of IDR 694,188,150 or 7.10%. This can be a consideration in making decisions for prediction results using Recurrent Neural Network.

Item Type: Thesis (Skripsi)
Additional Information: [No.Panggil: 2010312063] [Pembimbing: Yulizar Widiatama] [Penguji 1: Nur Fajriah] [Penguji 2: Donny Montreano]
Uncontrolled Keywords: Forecasting, Sparepart, Recurrent Neural Network
Subjects: T Technology > T Technology (General)
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Fakultas Teknik > Program Studi Teknik Industri (S1)
Depositing User: HISYAM RAKA PRASNANTYO
Date Deposited: 02 Aug 2024 08:11
Last Modified: 05 Aug 2024 05:54
URI: http://repository.upnvj.ac.id/id/eprint/31777

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