Analisis Fast Moving Consumer Goods untuk Memprakirakan Penjualan Barang Menggunakan Metode Triple Exponential Smoothing
| Autor: | Nanda Hafiz Ar, Muchamad Kurniawan |
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| Rok vydání: | 2021 |
| Předmět: | |
| Zdroj: | INTEGER: Journal of Information Technology. 6 |
| ISSN: | 2579-566X 2477-5274 |
| DOI: | 10.31284/j.integer.2021.v6i2.2311 |
| Popis: | Fast Moving Consumer Goods (FMCG) refers to a business sector generating economy particularly in Indonesia. The movement of goods runs quickly as they belong to staple food and have relatively short shelf life. They are sometimes unpredictable and even out of stock specifically to goods in fast moving category. Consequently, business doers can lose opportunities. Therefore, sale prediction is necessary to reduce opportunity loss and stock piling upon the goods that should not be ordered excessively. This research conducted prediction through Triple Exponential Smoothing method in the period of January 2018 to June 2020 by taking 5 item samples that were then tried out using alpha 0.1 – 0.9. As a result, alpha 0.1 became the best alpha in this research compared to alpha 0.2 – 0.9. Out of 5 trials, alpha 0.1 (MAPE 22%, 19%, and 34%) occurred three times and alpha 0.2 (MAPE 34% and 11%) happened twice. However, this research has not obtained the best result yet as it has not satisfied the indicator of more than 10% whole MAPEs. Thus, Triple Exponential Smoothing Brown was less appropriate to the data being used. The calculation of estimation did not consider the data fluctuation such as Ramadhan event greatly affecting the data training and forecasting result |
| Databáze: | OpenAIRE |
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