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Analisis Metode Peramalan Permintaan UMKM Pakaian Pada Platform E-Commerce
Accurate demand forecasting is one of the biggest challenge for SME in e-commerce, including for Pink Fashion which is an online muslim fashion store from Jakarta. Thus, this study is analysing various simple time series demand forecasting methods such as moving average (MA), weighted moving average (WMA), simple exponential smoothing (SES), holt’s model, and seasonal index. Forecasting is done for the last one year, April 2021 to March 2022 using the last three years data on two of the store’s most best selling products, baju koko and training set. The result shows that SES with constant of 0,7 and WMA are the most suitable methods to forecast baju koko since they have the smallest MAPE score, 28,43% and 28,44% consecutively. The same methods as well as holt’s model are also chosen as the best methods to forecast the training set because they have the lowest MAPE score of 30,85%, 30,91%, and 30,95%. This shows that these two methods are proven as the best methods to estimate daily demand of fashion product in e-commerce. Using the chosen forecasting methods, Pink Fashion is predicted to get 282 and 283 demand of baju koko and 116, 115 and 115 demand of the training set in 1 April 2022..Ada Tabel
Ketersediaan
| Call Number | Location | Available |
|---|---|---|
| 13607 | PSB lt.2 - Karya Akhir | 1 |
| Penerbit | Depok Program Studi Manajemen Fakultas Ekonomi dan Bisnis UI., 2022 |
|---|---|
| Edisi | - |
| Subjek | Commerce E Forecasting Small and Medium Enterprise |
| ISBN/ISSN | - |
| Klasifikasi | - |
| Deskripsi Fisik | xiv, 125 p. ; diagr. ; 30 cm |
| Info Detail Spesifik | - |
| Other Version/Related | Tidak tersedia versi lain |
| Lampiran Berkas | Tidak Ada Data |