Forecasting Analysis of Warp Yarn Production Using Holt’s and Holt-Winter’s Exponential Smoothing Using Golden Section Optimization
Analisa Produksi Benang Lusi dengan Metode Holt-dan Holt-Winter’s Exponential Smoothing dengan Optimasi Golden Section
DOI:
https://doi.org/10.21070/ups.2021Keywords:
Double Exponential Smoothing, Holt-Winter’s Exponential Smoothing, golden section, production forecastingAbstract
PT. XY is a company active in the textile industry. During religious celebrations in the islamic calendar, companies often experience fluctuating demand. This has an impact on increasing production, 30% occured at PT. XY during the month of Ramadhan 2023 and fluctuations continue until the end of the first quarter. In this situation, the availability of warp yarn as the main ram material is still insufficient to meet the demand. This study aims to predict the productions of warp yarn in the next twelve periods by evaluating the average absolute error rate (MAPE) of the Double Exponential Smoothing Holt’s (DES) and Holt-Winter’s Exponential Smoothing (WES) methods which will be combined with the golden section optimization method. As a result, the best forecasting method with the smallest standard error of 5,5437% is WES method with a combination of golden section parameters α1 = 0,67387, β1 = 0,08756, and γ2 = 0,85408.
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