Perancangan Demand Forecast untuk Suku Cadang Cartridge Excavator Menggunakan Metode Adaptive Neuro Fuzzy Inference System (ANFIS) Berdasarkan Faktor Ekonomi dan Cuaca

Kelasworo, Marsa Adyaninggar (2022) Perancangan Demand Forecast untuk Suku Cadang Cartridge Excavator Menggunakan Metode Adaptive Neuro Fuzzy Inference System (ANFIS) Berdasarkan Faktor Ekonomi dan Cuaca. Other thesis, Institut Teknologi Sepuluh Nopember.

Text 02311840000127-Undergraduate_Thesis.pdf - Accepted Version Download (3MB)

Abstract

Proses pengadaan persediaan suku cadang cartridge pada excavator menjadi salah satu tantangan yang dialami PT. XYZ, akibat angka demand suku cadang yang sangat fluktuatif dan pola demand suku cadang yang tidak menentu. Peneliti melakukan perancangan model demand forecast suku cadang cartridge excavator untuk meningkatkan pelayanan purna jual dalam ketepatan waktu penyediaan suku cadang cartridge bagi pelanggan dan meningkatkan keuntungan yang optimal bagi PT. XYZ. Peneliti menggunakan metode Adaptive Neuro Fuzzy Inference System (ANFIS) dengan variabel input yaitu harga jual suku cadang, PDB, dan lama penyinaran matahari. Performansi metode demand forecast yang diusulkan yaitu ANFIS, dibandingkan dengan metode demand forecast yang digunakan oleh PT. XYZ yaitu Moving Average. Hasil uji akurasi menunjukkan nilai error ANFIS untuk kedua tipe cartridge secara berurutan sebesar MAD 2.80 dan 7.24, MSE 15.03 dan 87.04. Metode Moving Average menghasilkan nilai error sebesar MAD 4.82 dan 9.30, MSE 53.02 dan 234.68. Kesimpulan yang didapatkan yaitu metode ANFIS adalah metode demand forecast dengan performansi atau tingkat akurasi yang lebih baik daripada metode Moving Average.
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The highly volatile demand for spare parts and the uncertain pattern of spare parts demand caused the process of procuring spare parts for cartridges on excavators is one of the challenges experienced by PT. XYZ. The researcher designed a demand forecast model for excavator cartridge spare parts using the Adaptive Neuro Fuzzy Inference System (ANFIS) method with input variables, selling price, GDP, and duration of sunlight. In this study, the performance of ANFIS is compared with the demand forecast method used by PT. XYZ i.e. Moving Average (MA). From the results of the accuracy test, the ANFIS error values for both types of cartridges are MAD 2.80 and 7.24, MSE 15.03 and 87.04. Meanwhile, with the Moving Average method, the error values are MAD 4.82 and 9.30, MSE 53.02 and 234.68. So it can be concluded that the ANFIS method is a demand forecast method with better performance or accuracy than the Moving Average method.

Item Type:	Thesis (Other)
Additional Information:	RSF 629.836 Kel p-1 2022
Uncontrolled Keywords:	Adaptive Neuro Fuzzy Inference System (ANFIS), Demand Forecast, Moving Average (MA), Suku Cadang Cartridge, Adaptive Neuro Fuzzy Inference System (ANFIS), Cartridge Spare Parts, Demand Forecast, Moving Average (MA)
Subjects:	T Technology > TJ Mechanical engineering and machinery > TJ217 Adaptive control systems
Divisions:	Faculty of Industrial Technology and Systems Engineering (INDSYS) > Physics Engineering > 30201-(S1) Undergraduate Thesis
Depositing User:	- Davi Wah
Date Deposited:	27 Sep 2024 08:45
Last Modified:	27 Sep 2024 08:45
URI:	http://repository.its.ac.id/id/eprint/115681

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