Klasifikasi Penjualan Perhiasan Menggunakan Metode Decision Tree Algoritma C4.5 (Studi Kasus: Toko Emas Berkat Famili)

Jewelry sales classification using Decision Tree Method with C4.5 Algorithm at Berkat Famili Gold Shop can facilitate and assist the store in obtaining information on the classification of sales of goods that are most in demand (in demand) and those that are less in demand (less in demand) from the results of sales data processing. The aspects or attributes used as parameters for the classification process are item type, item name, price, weight per gram, grade, inventory, sales, and sales status. Of the 14 test data used, the results of rule formation were obtained as many as 8 rules. Based on the results of rule formation, it is obtained that the most popular items (in demand) are Indian earrings, plain rings, rice necklaces, crystal earrings if the price is more than Rp. 726667, model rings if the weight is more than 2gram. Based on the system tests that have been carried out, it can be concluded that the functional of the jewelry sales classification application at Berkat Famili Gold Shop can has run well and can provide the results of the classification of sales of goods automatically through the C4.5 Method.

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Publication Details

Journal
JURNAL MEDIA INFOTAMA
Published
2024-10-17
DOI
https://doi.org/10.37676/jmi.v20i2.6517
Primary Topic
Data Mining and Machine Learning Applications
Type
article
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article

Klasifikasi Penjualan Perhiasan Menggunakan Metode Decision Tree Algoritma C4.5 (Studi Kasus: Toko Emas Berkat Famili)

Khairil Khairil, Herlina Latipa Sari, Herizal Syafputra
JURNAL MEDIA INFOTAMA
Data Mining and Machine Learning Applications
article

Klasifikasi Penjualan Perhiasan Menggunakan Metode Decision Tree Algoritma C4.5 (Studi Kasus: Toko Emas Berkat Famili)

Khairil Khairil, Herlina Latipa Sari, Herizal Syafputra
article en

Abstract

Jewelry sales classification using Decision Tree Method with C4.5 Algorithm at Berkat Famili Gold Shop can facilitate and assist the store in obtaining information on the classification of sales of goods that are most in demand (in demand) and those that are less in demand (less in demand) from the results of sales data processing. The aspects or attributes used as parameters for the classification process are item type, item name, price, weight per gram, grade, inventory, sales, and sales status. Of the 14 test data used, the results of rule formation were obtained as many as 8 rules. Based on the results of rule formation, it is obtained that the most popular items (in demand) are Indian earrings, plain rings, rice necklaces, crystal earrings if the price is more than Rp. 726667, model rings if the weight is more than 2gram. Based on the system tests that have been carried out, it can be concluded that the functional of the jewelry sales classification application at Berkat Famili Gold Shop can has run well and can provide the results of the classification of sales of goods automatically through the C4.5 Method.

JURNAL MEDIA INFOTAMAVol. 20(2)
Universitas Dehasen Bengkulu (ID)
Openalex Percentile: Top 62%
Data Mining and Machine Learning Applications
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