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

  • Herizal Syafputra Universitas Dehasen Bengkulu
  • Herlina Latipa Sari Universitas Dehasen Bengkulu
  • Khairil Khairil Universitas Dehasen Bengkulu
Keywords: Classification, Jewelry Sales, Decision Tree Method, C4.5 Algorithm

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.

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References

Christin Nandari Dengen, Kusrini, Emha Taufiq Luthfi. (2020). Implementasi Decision Tree Untuk Prediksi Kelulusan Mahasiswa Tepat waktu, Vol. 10 No. 1 Januari 2020 p-ISSN : 2087-7897, e-ISSN : 2460-5344

Cyntia, C., & Pudja, I. P. 2018. Subsidence analysis in DKI Jakarta using Differential Interferometry Synthetic Aperture Radar (DInSAR) Method. Sustinere: Journal of Environment and Sustainability, 2(3), 118-127.

Enda Suhenda, 2020. Klasifikasi Penjualan Makanan Cepat Saji Menggunakan Metode Algoritma C4.5 (Studi Kasus : Ayam Penyet Nabila), Universitas Pelita Bangsa. Kabupaten Bakasi

Gupitha, R. (2018). Penentuan Strategi Marketing Sekolah Menengah Kejuruan Terpadu Lampang Subang Menggunakan Metode K-Means Clustering. In Global (Vol. 5, No. 2).

Lasminiasih, 2018. Perancangan Sistem Informasi Kredit Mikro Mahasiswa Berbasis Web. Jurnal Sistem Informasi (JSI) Vol.8 No.1 April 2016 ISSN : 2085-1588.

Lubis, A., 2016. Basis Data Dasar Untuk Mahasiswa Ilmu Komputer. Yogyakarta: Deepublish.

Sikumbang, E. D. 2018. Penerapan data mining penjualan sepatu menggunakan metode algoritma apriori. Jurnal Teknik Komputer AMIK BSI, 4(1), 156-161.

Sukma, Halfis, dan Hermawan. (2019). Klasifikasi Channel Youtube Indonesia Menggunakan Algoritma C4.5, Volume V No. 1 Februari 2019 P-ISSN 2442-2436, E-ISSN: 2550-0120

Wanto, A., Siregar, M. N. H., Windarto, A. P., Hartama, D., Ginantra, N. L. W. S. R., Napitupulu, D., ... & Prianto, C. 2020. Data Mining: Algoritma dan Implementasi. Yayasan kita menulis.

Winarti, T., Priyanto, D., Vydia, V., & Indriyawati, H. 2020. Penerapan Data Mining Menggunakan Algoritma Naive Bayes Untuk Klasifikasi Perpanjangan Kontrak Kerja Karyawan. In Seminar Nasional Hasil Penelitian dan Pengabdian Kepada Masyarakat (pp. 288-301).

Published
2024-10-17
How to Cite
Syafputra, H., Sari, H., & Khairil, K. (2024). Klasifikasi Penjualan Perhiasan Menggunakan Metode Decision Tree Algoritma C4.5 (Studi Kasus: Toko Emas Berkat Famili). JURNAL MEDIA INFOTAMA, 20(2), 563-569. https://doi.org/10.37676/jmi.v20i2.6517
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Articles