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All Journal Journal of Artificial Intelligence and Engineering Applications (JAIEA)
Adila G Khiqmatiar Muchsin
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Automotive Engineering Computer Science & IT Control & Systems Engineering

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Application of Decision Tree Algorithms to Classify the Sales Results of Kangen Kripik Sme Products Adila G Khiqmatiar Muchsin; Nining Rahaningsih; Irfan Ali; Dadang Sudrajat; Saeful Anwar
Journal of Artificial Intelligence and Engineering Applications (JAIEA) Vol. 5 No. 2 (2026): February 2026
Publisher : Yayasan Kita Menulis

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59934/jaiea.v5i2.1854

Abstract

Micro, Small, and Medium Enterprises (MSMEs) play a vital role in strengthening the national economy; however, many still face challenges in managing and analyzing sales data effectively. This study aims to classify product sales results at UMKM Kangen Kripik Mang Acep by applying the Decision Tree algorithm as a data classification method based on machine learning. A quantitative experimental approach was employed to evaluate the model’s performance using one-year sales data, including attributes such as product variants, sales volume, sales channels, and marketing regions. Data processing was conducted using RapidMiner software following the Knowledge Discovery in Databases (KDD) framework, which includes data selection, preprocessing, transformation, data mining, and model evaluation. The results indicate that the Decision Tree algorithm successfully classified sales regions (Garut, Bandung, and Sumedang) with an accuracy rate of 96.48%, identifying “Units Sold (pcs)” as the most influential attribute for distinguishing marketing areas. These findings demonstrate that the Decision Tree method is not only effective in improving data analysis efficiency but also provides valuable strategic insights for data-driven business decision-making in MSMEs
Co-Authors Dadang Sudrajat Irfan Ali Nining Rahaningsih Saeful Anwar