Please use this identifier to cite or link to this item: http://repository.ipb.ac.id/handle/123456789/154244
Title: Analisa Perhitungan Permintaan Menggunakan Forecast dan Agregat Berbasis Seasonal Demand pada Produk LY34 di PT OMI
Other Titles: Demand Calculation Analysis Using Forecast and Aggregate Based on Seasonal Demand for LY34 Products at PT OMI.
Authors: Hidayat, Agung Prayudha
Zahran, Fadhil Rizqi Az
Issue Date: 2024
Publisher: IPB University
Abstract: Dalam dunia manufaktur yang dinamis, perkiraan permintaan yang tepat sangat penting untuk mengoptimalkan rantai pasokan dan proses produksi. Studi ini bertujuan untuk meningkatkan akurasi peramalan permintaan dan mengurangi biaya produksi di PT Omron Manufacturing of Indonesia. Dengan menggunakan metode Multiplicative Decomposition - Centered Moving Average dan Perencanaan Agregat Metode Transportasi, hasil menunjukkan peningkatan dalam prediksi permintaan, meskipun iterasi diperlukan. Hasil peramalan untuk periode berikutnya adalah 1308 unit dengan MAPE 140%. Kesimpulan studi ini menekankan pentingnya iterasi dalam memilih metode peramalan untuk mencapai akurasi yang lebih tinggi. Selain itu, hasil peramalan digunakan dalam perencanaan agregat untuk menghasilkan biaya produksi minimum sebesar Rp480.867.780,-, yang akan meningkatkan efisiensi produksi dan mencegah kekurangan suku cadang di industri manufaktur.
In the dynamic world of manufacturing, precise demand forecasting is critical to optimizing supply chains and production processes. This study aims to increase the accuracy of demand forecasting and reduce production costs at PT Omron Manufacturing of Indonesia. By using the Multiplicative Decomposition - Centered Moving Average method and the Aggregate Transportation Planning Method, the results show improvements in demand prediction, although iteration is required. The forecast results for the next period are 1308 units with a MAPE of 140%. The conclusion of this study emphasizes the importance of iteration in selecting forecasting methods to achieve higher accuracy. In addition, the forecasting results are used in aggregate planning to produce a minimum production cost of IDR 480,867,780,-, which will increase production efficiency and prevent spare parts shortages in the manufacturing industry.
URI: http://repository.ipb.ac.id/handle/123456789/154244
Appears in Collections:UT - Industrial Management

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