Please use this identifier to cite or link to this item: https://repository.unej.ac.id/xmlui/handle/123456789/124733
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dc.contributor.authorMADANI, Anis-
dc.date.accessioned2025-01-13T03:05:35Z-
dc.date.available2025-01-13T03:05:35Z-
dc.date.issued2023-07-20-
dc.identifier.nim172410102081en_US
dc.identifier.urihttps://repository.unej.ac.id/xmlui/handle/123456789/124733-
dc.description.abstractCafe 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.sponsorship1. Yanuar Nurdiansyah, ST., M.Cs. 2. Muhammad ‘Ariful Furqon, S.Pd, M.Komen_US
dc.publisherFakultas Ilmu Komputeren_US
dc.subjectprediksi penjualanen_US
dc.subjectExtreme Learning Machineen_US
dc.subjectMean Absolute Percentage Erroren_US
dc.subjectMean Absolute Deviationen_US
dc.titlePrediksi menggunakan Metode Extreme Learning Machine untuk Penjualan Produk Kopi Bubuk (Studi Kasus Kafe Tjap Daoen Bondowoso)en_US
dc.typeSkripsien_US
dc.identifier.prodiTeknologi Informasien_US
dc.identifier.pembimbing1Yanuar Nurdiansyah, ST., M.Cs.en_US
dc.identifier.pembimbing2Muhammad ‘Ariful Furqon, S.Pd, M.Komen_US
dc.identifier.validatorvalidasi_repo_ratna_Oktober_2024en_US
dc.identifier.finalization0a67b73d_2025_01_tanggal 13en_US
Appears in Collections:UT-Faculty of Computer Science

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