Penerapan Metode Naïve Bayes dalam Sistem Restock Barang pada Toko Ffactory2nd

  • Ricky Laschka Zidane Santoso Universitas Nusantara PGRI Kediri
  • Risa Helilintar Universitas Nusantara PGRI Kediri
  • Patmi Kasih Universitas Nusantara PGRI Kediri
https://doi.org/10.29407/noe.v7i01.21964
Abstract views: 56 , PDF downloads: 41
Keywords: Naive Bayes, PenentuanRestock, Flactory2nd, Barang, Prediksi

Abstract

This research aims to implement the Naïve Bayes method in determining restocking decisions for Ffactory2nd, a fashion product retail business entity. Ffactory2nd has a crucial need to effectively manage its inventory and make informed decisions regarding restocking. Sales data were collected from August to December 2023, with testing conducted on 16 selected products as samples. The analysis results indicate that the system can provide accurate restocking recommendations based on inventory levels. The Naïve Bayes method is employed for classifying restocking into two categories: Restock (Yes) and No Restock. The analysis demonstrates that the system is capable of delivering accurate restocking recommendations, aiding inventory managers in more effective decision-making. Alpha and beta functional testing indicates that the restocking determination system has been successfully implemented and well-received by users. User satisfaction reached an average level of 93%, indicating a positive impact of the system on inventory management at Ffactory2nd.

References

Aminudin, N., & Sari, I. A. P. (2017). Sistem Pendukung Keputusan (DSS) Penerima Bantuan Program Keluarga Harapan (PKH) Pada Desa Bangun Rejo Kec. Punduh Pidada Pesawaran Dengan Menggunakan Metode Analytical Hierarcy Process (AHP). Jurnal TAM (Technology Acceptance Model), Vol. 5, 66-72. (Online)
Arifin, S., & Helilintar, R. (2022, August). Sistem Pendukung Keputusan Penentuan ReStock Barang Dengan Metode Naive Bayes. In Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi), Vol. 6, No. 2, pp. 259-264. (Online)
Ayuningtyas, N., Nining, R., & Basysyar, F. M. (2022). Penerapan Data Mining pada Penjualan Produk MS Glow Menggunakan Metode Naive Bayes untuk Strategi Pemasaran. Jurnal Accounting Information System (AIMS), 5(2), 157-166. (Online)
Damara, M. D. S., Farida, I. N., & Sahertian, J. (2021, August). Sistem Prediksi Minat Penjualan Jaket di Grosir Murah Kediri Menggunakan Metode Naive Bayes. In Prosiding SEMNAS INOTEK (Seminar Nasional Inovasi Teknologi), Vol. 5, No. 1, pp. 309-314. (Online)
Erfina, A. (2021). Buku Ajar Data Mining. Nusa Putra Press.
Ferdika, M., & Kuswara, H. (2017). Sistem Informasi Penjualan Berbasis Web Pada PT Era Makmur Cahaya Damai Bekasi. Information System For Educators And Professionals: Journal of Information System, 1(2), 175-188. (Online)
ffactory2nd. (2024). KEDIRI | THRIFT KEMEJA OPEN COLLAR SHIRT JAKET VTG. Instagram.
Hutahaean, M. (2022). Penerapan Data Mining untuk Memprediksi Penjualan Obat di Klinik Harapan Kita Batam. Doctoral dissertation, Prodi Teknik Informatika. (Online)
Pratama, F. D., Zufria, I., & Triase, T. (2022). Implementasi Data Mining Menggunakan Algoritma Naïve Bayes Untuk Klasifikasi Penerima Program Indonesia Pintar. Rabit: Jurnal Teknologi dan Sistem Informasi Univrab, 7(1), 77-84. (Online)
Mubarrizi, N. M. (2023). Sistem Informasi Pengelolaan Persediaan Bahan Produksi Dan Pembayaran Tagihan Menggunakan Metode Periodic Review Pada Ben’s Bakery Berbasis Web. Jurnal SITECH: Sistem Informasi dan Teknologi, 6(1), 33-44.

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Published
2024-05-05
How to Cite
Santoso, R. L. Z., Helilintar, R., & Kasih, P. (2024). Penerapan Metode Naïve Bayes dalam Sistem Restock Barang pada Toko Ffactory2nd. Nusantara of Engineering (NOE), 7(1), 29 - 37. https://doi.org/10.29407/noe.v7i01.21964
Issue
Vol. 7 No. 1 (2024): Volume 7 No. 1 Tahun 2024
Section
Artikel

Copyright (c) 2024 Ricky Laschka Zidane Santoso Ricky, Risa Helilintar Risa, Patmi Kasih Patmi

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