Open AccessIMPLEMENTASI ALGORITMA DECISION TREE UNTUK KLASIFIKASI PRODUK LARIS
Author(s) -
Asmaul Husnah Nasrullah
Publication year - 2021
Publication title -
jurnal ilmiah ilmu komputer fakultas ilmu komputer universitas al asyariah mandar/jurnal ilmiah ilmu komputer
Language(s) - English
Resource type - Journals
eISSN - 2503-3832
pISSN - 2442-451X
DOI - 10.35329/jiik.v7i2.203
Subject(s) - decision tree , incremental decision tree , decision tree learning , id3 algorithm , computer science , data mining , product (mathematics) , tree (set theory) , c4.5 algorithm , artificial intelligence , machine learning , mathematics , support vector machine , naive bayes classifier , mathematical analysis , geometry
Decision Tree C4.5 algorithm is an algorithm that can be used to make a decision tree. Decision tree (Decision Tree) is one method that is quite easily interpreted by humans. However, this algorithm has never been tested for product classification using private data (stock data and sales of goods at PT Cipta Karya Gorontalo). Therefore this study aims to test the accuracy of C4.5 in classifying best-selling products (private data). As a result of the evaluation of product classification models using Decision Tree C4.5 obtained from this study amounted to 90% and AUC value of 0.709 where this value is included in the Good Classification. It can be used as a data mining classification method Decision Tree C4.5 algorithm is accurate in classifying hot-selling products.
Keywords— Decision Tree, C4.5, Classification, Best-Selling Product