
ANALISIS PERAMALAN KEBUTUHAN PERSEDIAAN UNTUK KEUNGGULAN BERSAING PADA PERUSAHAAN ORCA
Author(s) -
Ratih Hedayani,
Rachmat Simbara Saputra,
Fariz Indra Permana,
Galang Nusa Mahardhika
Publication year - 2016
Publication title -
jurnal manajemen
Language(s) - English
Resource type - Journals
eISSN - 2541-4348
pISSN - 2088-7698
DOI - 10.26460/jm.v5i2.195
Subject(s) - demand forecasting , sales forecasting , inventory control , computer science , competitive advantage , supply chain , inventory management , operations management , operations research , statistics , business , mathematics , economics , marketing
Orca is a company that run in the field of handicrafts, mainly craft bracelet. In this era of tight competition this time, Orca needs a competitive advantage to survive in this industry. To have a competitive advantage, companies must have a good supply chain management as well. Unfortunately, Orca has obstacles in the inventory is one of the Drivers of suplly chain management. Inventories at Orca often occurs over load, causing storage costs become swollen or a vacancy occurs so that the company's stock experienced a loss of income potential. The aim of this study was to determine the best forecasting method to
forecast the demand for raw materials from ORCA thus making optimum inventory and gain a competitive advantage.
This research is a quantitative descriptive research. Quantitative data analysis was performed to predict the demand for raw materials ORCA using time series forecasting methods. Historical data demand and supply ORCA processed using Microsoft Excel and Minitab 17. The calculation of the error rate used is the method of MAD, MSE and MAPE.
Based on the results of data analysis, forecasting method best known is the method of Quadratic Trend Model. This method was chosen because compared to other methods or the error rate to its lowest error, MAPE of 103, amounting to MAD 370, and MSD amounted to 205.095.
Keywords: Forecasting, Inventory, Time Series, Competitive Advantage, Supply Chain Management.