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Silemberesen Silemberesen
Universitas Prima Indonesia
Computer Science & IT

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Triple Exponential Smoothing Analysis in Predicting Numbers Request for Delivery of Logistics CV. Lotus Mas Express Elvis Sastra Ompusunggu; Andrean Wirjana; Silemberesen Silemberesen; Dea Junia Dea Junia
INFOKUM Vol. 10 No. 02 (2022): Juni, Data Mining, Image Processing, and artificial intelligence
Publisher : Sean Institute

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Abstract

CV. Teratai Mas Express is a company engaged in services, namely transportation services or commonly called expeditions. But this company specializes in transportation logistics. The problem that is often faced by this company is that it often suffers losses due to being unstructured in terms of stock transportation inventory to the number of delivery requests. Especially in certain seasons and usually the corn harvest season. Demand rose, but companies often made mistakes in providing their freight. Sometimes advantages and sometimes disadvantages. Excess or shortage of these supplies in a high level. Suppose the company provides 14 transportations but only 8 is used or vice versa, resulting in a large loss. For this reason, a precise prediction calculation is needed so that the number of logistics delivery requests can be predicted efficiently in order to reduce large losses. The prediction method that I use is Triple Exponential Smoothing. This method is suitable for use in this case because the number of logistics delivery requests increases in certain seasons and this method can analyze it.
Co-Authors Andrean Wirjana Dea Junia Dea Junia Elvis Sastra Ompusunggu