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dc.contributor.advisorHasibuan, Citra Dewi
dc.contributor.authorTarigan, Valentino Adi Syahputra
dc.date.accessioned2024-08-29T07:54:25Z
dc.date.available2024-08-29T07:54:25Z
dc.date.issued2024
dc.identifier.urihttps://repositori.usu.ac.id/handle/123456789/96360
dc.description.abstractMula Kopi Medan is one of the business actors engaged in coffee shops. Sales fluctuations are a challenge for the management in providing raw material needs, this is due to the absence of forecasts for future sales. Single Exponential Smoothing and Least Square are forecasting methods that predict the value of a variable based on the value of the previous time. The results of the implementation of Single Exponential Smoothing predict 195 products sold in June 2024 and Least Square predicts 225 products. This states that these two methods can be used to forecast sales growth. The addition of data can optimize the Single Exponential Smothing and Least Square Methods to produce more precise and accurate predictions.en_US
dc.language.isoiden_US
dc.publisherUniversitas Sumatera Utaraen_US
dc.subjectSingle Exponential Smoothingen_US
dc.subjectLeast Squareen_US
dc.subjectForecastingen_US
dc.subjectSDGsen_US
dc.titlePenerapan Metode Single Eksponensial Smoothing dan Least Square untuk Memprediksi Penjualan Produk Kopi di Mula Kopi Medanen_US
dc.title.alternativeApplication of Single Exponential Smoothing and Least Square Methods to Predict Sales of Coffee Products at Mula Kopi Medanen_US
dc.typeThesisen_US
dc.identifier.nimNIM212407044
dc.identifier.nidnNIDN0003029302
dc.identifier.kodeprodiKODEPRODI49401#Statistika
dc.description.pages58 Pagesen_US
dc.description.typeKertas Karya Diplomaen_US


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