Penerapan Metode C4.5 dalam Prediksi Penjualan Tim Bev 1 pada PT. Surya Pangan Sejahtera Bekasi Jawa Barat
Original Full-Text Article
Download published version for reading and archivingAbstract
The C4.5 method is a machine learning algorithm used to create decision trees in data analysis. This research aims to apply the C4.5 Method in predicting the Bev Team 1 target sales at PT. Surya Pangan Sejahtera in Bekasi, West Java. This research utilizes historical sales data, internal and external factors that influence sales, as well as sales targets set by the company. The C4.5 method is used to produce a decision tree that can help in understanding the key factors that influence the sales of the Bev 1 team. The results of this research show that the C4.5 Method can be used to predict the sales of the Bev 1 team with fairly high accuracy. The decision tree generated by this algorithm helps identify the factors that most influence sales, such as sales location, season, promotions, and others. By understanding these factors, companies can take more effective action in achieving their sales targets. This research provides valuable insight for PT. Surya Pangan Sejahtera in managing the Bev 1 team and achieving their sales targets. The C4.5 method can be a useful tool in data analysis and future sales predictions, as well as helping companies to make better decisions in optimizing the performance of their Bev 1 teams.
Keywords:
Author Biographies
STIKOM Cipta Karya Informatika, Kota Jakarta Timur, Daerah Khusus Ibukota Jakarta, Indonesia.
STIKOM Cipta Karya Informatika, Kota Jakarta Timur, Daerah Khusus Ibukota Jakarta, Indonesia.
How to Cite
This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International License .
- Share: You are free to copy, distribute, and transmit the work in any medium or format.
- Adapt: You are free to remix, transform, and build upon the work for any purpose, even commercially.
- Attribution: You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
References
Total: 24 References- Ahmed, H., & Nandi, A. K. (2020). Condition monitoring with vibration signals: Compressive sampling and learning algorithms for rotating machines. John Wiley & Sons.
- Anggraini, S., Defit, S., & Nurcahyo, G. W. (2018). Analisis Data Mining Penjualan Ban Menggunakan Algoritma C4. 5. Jurnal Ilmu Teknik Elektro Komputer dan Informatika (JITEKI), 4(2), 136..
- Ardiansyah, D. (2019). Algoritma c4. 5 untuk klasifikasi calon peserta lomba cerdas cermat siswa smp dengan menggunakan aplikasi rapid miner. Jurnal Inkofar, 1(2). DOI: https://doi.org/10.46846/jurnalinkofar.v1i2.29.
- Arif, A., & Yulianto, A. (2022). Klasifikasi Penjualan Makanan Hewan Peliharaan di Muezza Petshop01 Bogor Menggunakan Metode Algoritma C4. 5. REMIK: Riset dan E-Jurnal Manajemen Informatika Komputer, 6(4), 840-854. DOI: https://doi.org/10.33395/remik.v6i4.11859.
- Arifin, M. F., & Fitrianah, D. (2018). Penerapan Algoritma Klasifikasi C4. 5 Dalam Rekomendasi Penerimaan Mitra Penjualan Studi Kasus: PT Atria Artha Persada. InComTech: Jurnal Telekomunikasi dan Komputer, 8(2), 87-102. DOI: https://doi.org/10.22441/incomtech.v8i1.2198.
Similar Articles
Articles sharing related keywords and machine learning classifications: