Peramalan Persediaan Suku Cadang Menggunakan Integrasi Arima-Fuzzy EOQ (Studi Kasus: PT XYZ)

Ramadhan, Alfian Putra (2022) Peramalan Persediaan Suku Cadang Menggunakan Integrasi Arima-Fuzzy EOQ (Studi Kasus: PT XYZ). Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Peramalan permintaan sangat penting bagi hampir semua perusahaan termasuk pada PT XYZ. Keakuratan dalam memprediksi permintaan suku cadang memberikan gambaran input data yang optimal untuk mengoptimalkan total biaya dalam proses persediaan. Namun, kebutuhan suku cadang tidak selalu menentu dalam waktu tertentu. Suku cadang dibutuhkan jika terjadi kerusakan pada barang yang bersangkutan, tetapi waktu terjadi kerusakan merupakan hal yang tidak pasti. Dalam penelitian ini diprediksi permintaan kebutuhan suku cadang pada PT XYZ menggunakan metode ARIMA (Autoregressive Integrated Moving Average) dan fuzzy EOQ (Economic Order Quantity). Model ARIMA berbasis time series mampu meramalkan pola data historis. Dengan menggunakan data masa lampau pada PT XYZ sebagai model data awal, didapatkan model ARIMA yang sesuai. Selanjutnya dilakukan klasifikasi dengan menggunakan analisa klasifikasi ABC-fuzzy. Dengan analisa klasifikasi ABC-fuzzy didapatkan kategori kelas untuk setiap jenis suku cadang dan penentuan model EOQ yang digunakan. Hasil akhir didapatkan kuantitas pemesanan dan titik pemesanan kembali yang optimal serta total biaya persediaan minimum.
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Demand forecasting is very important for almost all companies including PT XYZ. Accuracy in predicting parts demand provide an optimal picture of data input to optimize total costs in the inventory process. However, the need for spare parts is not always erratic within a certain time. Spare parts are needed in case of damage to the goods concerned, but the time of the damage is uncertain. In this study, it was predicted the demand for spare parts needs at PT XYZ using the ARIMA (Autoregressive Integrated Moving Average) method and fuzzy EOQ (Economic Order Quantity). The time series-based ARIMA model is able to foresee historical data patterns. By using past data on PT XYZ as the initial data model, the appropriate ARIMA model was obtained. Furthermore, classification was carried out using ABC-fuzzy classification analysis. With ABC-fuzzy classification analysis, a class category was obtained for each type of spare part and the determination of the EOQ model used. The final result is obtained the optimal quantity of orders and reorder points as well as the total minimum inventory costs.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Suku Cadang, Peramalan, Model ARIMA, Klasifikasi ABC-Fuzzy, EOQ, Sistem Peninjauan Berkelanjutan, Kuantitas Pemesanan, Total Biaya Minimum, Spare Parts, Forecasting, ARIMA Model, ABC-Fuzzy Classification, EOQ, Continuous Review System, Quantity Order, Minimum Total Cos,
Subjects:	Q Science > QA Mathematics > QA280 Box-Jenkins forecasting
Divisions:	Faculty of Science and Data Analytics (SCIENTICS) > Mathematics > 44201-(S1) Undergraduate Thesis
Depositing User:	Mr. Marsudiyana -
Date Deposited:	22 Oct 2025 02:31
Last Modified:	22 Oct 2025 02:31
URI:	http://repository.its.ac.id/id/eprint/128658

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