Penerapan Data Mining untuk Menentukan Produk Terlaris pada PT Joynare Mitra Teknologi menggunakan Metode Naive Bayes
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The research applies the Naive Bayes method to determine the best-selling products at PT Joynare Mitra Teknologi. The contribution of this research is to provide a reference for other companies interested in using similar techniques to analyze their product data. Testing was carried out by processing data using Microsoft Excel and RapidMiner, with training and testing data. The test results show that the Naive Bayes method can classify best-selling products with a high level of accuracy, reaching 87.00%. Apart from that, the resulting precision reached 72.41%, and recall was 80.77%. The best-selling products in hardware sales such as motherboards, CPUs, RAM, hard disks, SSD, and printers can be identified through data analysis. The conclusion from the research is that the Naive Bayes method is very appropriate to use to optimize sales strategies for hardware products based on customer preferences.
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Handayani, K., Lisnawanty, L., Latif, A., Firdaus, M. R., & Hasan, F. N. (2021). Komparasi Algoritma C4. 5 dan Naïve Bayes dalam Penentuan Status Kelayakan Donor Darah. SISTEMASI, 10(3), 676-687. DOI: https://doi.org/10.32520/stmsi.v10i3.1440.
Lubis, C. P., Rosnelly, R., Roslina, R., Situmorang, Z., & Wanayumini, W. (2021). Penerapan Metode Naïve Bayes dan C4. 5 Pada Penerimaan Pegawai di Universitas Potensi Utama. CSRID (Computer Science Research and Its Development Journal), 12(1), 51-63. DOI: 10.22303/csrid.12.1.2020.51-63.
Nawangsih, I., & Sahar, J. (2022). Penerapan Data Mining Untuk Analisa Kualitas Produk Welding Dengan Algoritma Naïve Bayes Dan C4. 5 Pada PT. Karya Bahana Unigam. Jurnal SIGMA, 13(1), 21-26.
Niar, Y., Komariah, K., Surip, A., Saputra, R., & Ali, I. (2020). Implementasi Algoritma Naïve Bayes Untuk Prediksi Persediaan Barang Rotan. KOPERTIP: Scientific Journal of Informatics Management and Computer, 4(1), 28-34. DOI: https://doi.org/10.32485/kopertip.v4i1.112.
Palupi, E. S., & Pahlevi, S. M. (2020). Klasifikasi Opportunity Menggunakan Algoritma C4. 5, C4. 5 Dan Naïve Bayes Berbasis Particle Swarm Optimization. Inti Nusa Mandiri, 14(2), 233-238. DOI: https://doi.org/10.33480/inti.v14i2.1178.
Qisthiano, M. R. (2023, January). PENERAPAN MODEL KLASIFIKASI NAÏVE BAYES UNTUK PREDIKSI MAHASISWA TEPAT WAKTU. In Semnas Ristek (Seminar Nasional Riset dan Inovasi Teknologi) (Vol. 7, No. 1). DOI: https://doi.org/10.30998/semnasristek.v7i1.6266.
Rafly, A., Hartono, R., Mulyawan, M., Nurdiawan, O., & Anwar, S. (2022). Perbandingan Algoritma C. 45 Dengan Naive Bayes Untuk Menentukan Introvert Dan Ekstrovert Pada Smk Bina Cendikia. INFORMATICS FOR EDUCATORS AND PROFESSIONAL: Journal of Informatics, 6(1), 74-83. DOI: https://doi.org/10.51211/itbi.v6i1.1687.
Ridwan, A., & Mundakir, S. (2020). Penerapan Teknik Bagging Pada Algoritma Naive Bayes Dan Algoritma C4. 5 Untuk Mengatasi Ketidakseimbangan Kelas. JURNAL ILMU KOMPUTER DAN MATEMATIKA, 1(1), 63-70.
Sukmawati, S., Sulastri, S., Februariyanti, H., & Jananto, A. (2022). Perbandingan Algoritma C4. 5 Dan Algoritma Naive Bayes Untuk Klasifikasi Pekerja Migran Indonesia. Informatika, 14(1), 7-16. DOI: http://dx.doi.org/10.36723/juri.v14i1.280.