| dc.contributor.author | MADANI, Anis | |
| dc.date.accessioned | 2025-01-13T03:05:35Z | |
| dc.date.available | 2025-01-13T03:05:35Z | |
| dc.date.issued | 2023-07-20 | |
| dc.identifier.nim | 172410102081 | en_US |
| dc.identifier.uri | https://repository.unej.ac.id/xmlui/handle/123456789/124733 | |
| dc.description.abstract | Cafe Tjap Daoen, has not used a method to support sales forecasting so that
the cafe only determines the sales of the cafe owner with reference to the previous
period without any calculations resulting in underproduction when busy,
overproduction of coffee when there are several orders. This study uses two Arabica
Specialty Coffee and Arabica Wine products with data for 2019 – 2022 respectively.
The Extreme Learning Machine (ELM) algorithm has very good performance in
predicting time series data. The results of the research conducted, the ELM
Algorithm is able to produce MAPE with a percentage of 1.2658% and MAD 3.1784
Arabica Specialty Coffee, Arabica Wine MAPE 10.373% MAD 3.5097. | en_US |
| dc.description.sponsorship | 1. Yanuar Nurdiansyah, ST., M.Cs.
2. Muhammad ‘Ariful Furqon, S.Pd, M.Kom | en_US |
| dc.publisher | Fakultas Ilmu Komputer | en_US |
| dc.subject | prediksi penjualan | en_US |
| dc.subject | Extreme Learning Machine | en_US |
| dc.subject | Mean Absolute Percentage Error | en_US |
| dc.subject | Mean Absolute Deviation | en_US |
| dc.title | Prediksi menggunakan Metode Extreme Learning Machine untuk Penjualan Produk Kopi Bubuk (Studi Kasus Kafe Tjap Daoen Bondowoso) | en_US |
| dc.type | Skripsi | en_US |
| dc.identifier.prodi | Teknologi Informasi | en_US |
| dc.identifier.pembimbing1 | Yanuar Nurdiansyah, ST., M.Cs. | en_US |
| dc.identifier.pembimbing2 | Muhammad ‘Ariful Furqon, S.Pd, M.Kom | en_US |
| dc.identifier.validator | validasi_repo_ratna_Oktober_2024 | en_US |
| dc.identifier.finalization | 0a67b73d_2025_01_tanggal 13 | en_US |
