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All Journal Electronic Integrated Computer Algorithm Journal
Reza Kavarin Telaumbanua
Politeknik Negeri Medan
Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Social Sciences

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Classification Analysis of Product Sales Results at Alfamart Using the Naïve Bayes Method Yuyun Yusnida Lase; Citra Wasti Silaban; Alex Sander Sitepu; Reza Kavarin Telaumbanua
Electronic Integrated Computer Algorithm Journal Vol. 1 No. 2 (2024): VOLUME 1, NO 2: APRIL 2024
Publisher : Yayasan Asmin Intelektual Berkah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.62123/enigma.v1i2.18

Abstract

This research focuses on the analysis of the number of products sold, especially stock items from the distribution center to Alfamart stores. The main problem discussed in this study is the result of the number of unsold and sold products, which causes overstocking in the warehouse area. To overcome this problem, it will be solved using the Naive Bayes classification method. This research uses sample data of 100 products and uses data collection techniques such as observation and interviews. The collected data is analysed through a classification approach. This research aims to predict goods that sell and do not sell using Rapidminer using the NaïveBayes method. And to produce more accurate data for the product sales process. The reason for using this naïve bayes algorithm in the process of processing and analysing data is because the way this algorithm works uses statistical methods and probability in predicting future results. The validation results show that the Naive Bayes classification method implemented through Rapidminer provides a significant explanation with a fairly high accuracy and a positive effect on the prediction of sales of goods based on consumer demand and needs.
Co-Authors Alex Sander Sitepu Citra Wasti Silaban Yuyun Yusnida Lase