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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika
Ramadhan, Alya Sophia
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Computer Science & IT

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Comparison Of Exponesial Smoothing With Linear Regression Predicting Amount Of Goods Sales Panggabean, Erwin; Sinaga, Anita Sindar Ros Maryana; Sagala, Jijon Raphita; Ramadhan, Alya Sophia; Josua, Alpon
Sinkron : jurnal dan penelitian teknik informatika Vol. 8 No. 3 (2024): Research Artikel Volume 8 Issue 3, July 2024
Publisher : Politeknik Ganesha Medan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33395/sinkron.v8i3.13811

Abstract

A trading business is a business that operates in the sales sector with the aim of obtaining maximum profits through sales activities. To be able to sell efficiently, a prediction system is needed, so that there is no excess or shortage of inventory and the sales process can run smoothly. Human limitations in solving prediction problems without using tools that apply prediction methods are one of the obstacles in finding the right prediction value. Therefore, we need a prediction system that can help find accurate and fast values. So the problem formulation is how to design and build a sales prediction system using exponential smoothing and linear regression methods, then compare the two and find out which method is the best, both of which use periodic data prediction models. The data collection method used is secondary data from previous research and journals, as well as combining library study methods, namely information obtained from books, references and scientific works related to predictions. The tool used to build applications is MS-Visual Studio 2010 and WEB based system
Co-Authors Erwin Panggabean Jijon Raphita Sagala, Jijon Raphita Josua, Alpon Sinaga, Anita Sindar Ros Maryana