IMPLEMENTASI DATA MINING UNTUK MEMPREDIKSI PENJUALAN PRODUK TERLARIS PADA PETSHOP MENGGUNAKAN ALGORITMA NAIVE BAYES
DOI:
https://doi.org/10.33884/comasiejournal.v11i2.9041Kata Kunci:
Knowledge Discovery in Databases (KDD); Data Mining; Naive Bayes, RapidMiner; PetshopAbstrak
In recent years, the petshop industry has seen a significant increase. This is due to people's growing awareness of pet welfare and the need for specialized products for them. Product sales in petshops are not only influenced by customer preferences, but also by the diversity of pet breeds, which makes data collection and product stock management more complex. Therefore, predicting the products that are most in demand by customers is important. Data mining, as a part of computer science that focuses on extracting information from data, offers an effective way to analyze patterns and trends of product sales in petshops. In this study, Naive Bayes algorithm is used to predict the best-selling products in petshop. RapidMiner software was used to process the data in this study. Data processing with RapidMiner resulted in a prediction accuracy of 90.41%. Class precision for the prediction of hot-selling products is 88.24%, while for non-selling products is 90.00%. Class recall for the prediction of hot-selling products reaches 90.91%, while for products that are not in demand reaches 92.31%.
Referensi
Aini, N., 1✉, H., Wijaya, K., Rahmanti, N., Kurnia, R., Ulyani, R., & Mufti, E. P. (2023). Implementasi Algoritma Naïve Bayes untuk Memprediksi Penjualan Lampu Pada Toko Satria. INNOVATIVE: Journal Of Social Science Research, 3, 9373–9387.
Saragih, S. P. (2018). Implementasi Platform Media Sosial Sebagai Business Support oleh Pelaku Usaha Wisata di Kota Batam. Journal of Applied Informatics and Computing, 2(2), 15–23. https://doi.org/10.30871/jaic.v2i2.1016
Bambang Seran, Y. (2024). ANALISIS SENTIMEN MASYARAKAT TERHADAP KINERJA KERJA PRESIDEN JOKO WIDODO MENGGUNAKAN ALGORITMA SUPPORT VECTOR MACHINE. In Jurnal Mahasiswa Teknik Informatika (Vol. 8, Issue 4).
Derajad Wijaya, H., & Dwiasnati, S. (2020). Implementasi Data Mining dengan Algoritma Naïve Bayes pada Penjualan Obat. JURNAL INFORMATIKA, 7(1).
Entini, A., Raja, L., & Handoko, K. (2023a). IMPLEMENTASI DATA MINING DENGAN ALGORITMA NAIVE BAYES UNTUK KLASIFIKASI KELAYAKAN PENERIMA BANTUAN SEMBAKO. In JURNAL COMASIE.
Felicia Watratan, A., Puspita, A. B., Moeis, D., Informasi, S., & Profesional Makassar, S. (2020). Implementasi Algoritma Naive Bayes Untuk Memprediksi Tingkat Penyebaran Covid-19 Di Indonesia. In JOURNAL OF APPLIED COMPUTER SCIENCE AND TECHNOLOGY (JACOST) (Vol. 1, Issue 1).
Handayani, Y., Hidayat, T., & Arruhama, H. (2023). Jurnal Teknik Informatika dan Desain Komunikasi Visual Implementasi Metode K-Nearest Neighbor Untuk Prediksi Penjualan Produk Terlaris Pada Toko Indah Jaya. Universitas Selamat Sri, 2(2).
Hidayat, B. (2022). Implementasi Data Mining Untuk Memprediksi Penjualan Pakaian Menggunakan Algoritma Naïve Bayes (Vol. 21).
Saragih, S. P. (2019). TECHNOLOGY ACCEPTANCE OF DIGITAL PAYMENT SYSTEM PADA PELAKU UMKM DI KOTA BATAM. Computer Based Information System Journal, 7(2), 82–90. https://doi.org/10.33884/cbis.v7i2.1402 Saragih, S. P., & Nopriadi, N. (2019). Pengaruh Budaya Terhadap Actual Use Digital Payment System Pada Pelaku UMKM di Kota Batam. Journal of Applied Informatics and Computing, 3(2), 63–67. https://doi.org/10.30871/jaic.v3i2.1646
Ronaldi, A. A., & Hunafi, N. (2020). IMPLEMENTASI DATA MINING UNTUK PREDIKSI PENJUALAN PESTISIDA PADA CV MITRA ARTHA SEJATI MENGGUNAKAN ALGORITMA NAIVE BAYES (Vol. 1, Issue 1).
