Implementasi Metode Decision Tree pada Sistem Prediksi Status Kualitas Produk Minuman A

Authors

  • Abdul Halim Anshor Universitas Pelita Bangsa
  • Ahmad Turmudi Zy Universitas Pelita Bangsa

DOI:

https://doi.org/10.36982/jiig.v15i1.3778

Abstract

The quality of a beverage product is one of the important items that beverage product entrepreneurs must pay attention to. Good quality beverage products will have an impact on consumers' health. UMKM Buah Sabar is one of the MSMEs located in Bekasi district which produces beverage products A. In the distribution of these beverage products, MSME workers in the delivery section have conditions where the product is out of stock or left over. The reseller must be able to understand whether the status of the remaining product is still of good quality or has been damaged. This is very important to pay attention to because the cooling conditions of each reseller have varying degrees of cold, sometimes also influenced by blackouts and unstable electricity voltage. This condition can cause the quality of product A to decrease. The large number of resellers and products sent will make it difficult for MSME workers to detect the quality of beverage product A. To overcome this problem the researchers found a solution that requires a machine learning method to predict the quality status of product A. In this research, the researchers used the decision tree method to predict the quality status of the product Drink A. The data used are 500 samples of drink product A in the production period from November 2023 to February 2024. The parameters used include temperature, color, taste, aroma, and quality status class of drink product A. The results of this research will show the presentation The accuracy value for the quality of product A is 99.59%, this shows that the decision tree algorithm has very good performance in the process of classifying the quality of beverage product A.

Published

2024-04-03

How to Cite

Anshor, A. H., & Zy, A. T. (2024). Implementasi Metode Decision Tree pada Sistem Prediksi Status Kualitas Produk Minuman A. Jurnal Ilmiah Informatika Global, 15(1), 17–22. https://doi.org/10.36982/jiig.v15i1.3778