Implementasi Naïve Bayes Dalam Pemilihan Jenis Bahan Pembuatan Meja
DOI:
https://doi.org/10.30646/sinus.v21i1.674Keywords:
Selection of Wood Types, Wood, Naive BayesAbstract
Wood is a very decisive main element in the furniture industry or other wood crafts. Furniture was originally an industry of furniture crafts and wood carvings, so that the furniture products produced highlighted the effect of art. To determine whether a wood is suitable or not as a furniture material, systematic and accurate calculations are needed in order to obtain the right decision making. From this problem the researcher implemented the Naïve Bayes method to classify the quality level of wood based on the probability of wood. This makes it easier for table manufacturers to choose wood based on the texture of the wood. The purpose of this study is to implement the Naïve Bayes method to classify the quality level of wood based on the probability of wood. The criteria used in this study include: wood texture, wood quality, wood age, wood diameter. The results of this study are in the form of a recommendation that the type of material was teak wood, the age of the wood was still young, the quality of the wood was good, the diameter of the wood was sufficient and the texture of the wood was smooth, the quality of the wood was suitable for use for raw materials for making tablesReferences
A. Ghofur, “Implementasi Metode Klasifikasi Naive Bayes Untuk Memprediksi Kualitas Cabai,†J. Ilm. Inform., vol. 1, no. 1, pp. 32–38, 2016, doi: 10.35316/jimi.v1i1.441.
bhinti khusnul khotimah, Sistem penentuan Kualitas Kayu Untuk Kerajianan Meubel Dengan Menggunakan Naive Bayes Di Meubel. Kediri: Universitas Nusantara PGRI Kediri, 2018.
Bustami, “Penerapan Algoritma Naive Bayes untuk Mengklasifikasi Data Nasabah,†TECHSI J. Penelit. Tek. Inform., vol. 4, pp. 127–146, 2010.
E. Manalu, F. A. Sianturi, and M. R. Manalu, “Penerapan Algoritma Naïve Bayes Untuk Memprediksi Jumlah Produksi Barang Berdasarkan Data Persediaan Dan Jumlah Pemesanan Pada CV. Papadan Mama Pastries,†J. Mantik Penusa, vol. 1, no. 2, 2017.
F. Y. Manik and K. S. Saragih, “Klasifikasi Belimbing Menggunakan Naïve Bayes Berdasarkan Fitur Warna RGB,†IJCCS (Indonesian J. Comput. Cybern. Syst., vol. 11, no. 1, p. 99, 2017, doi: 10.22146/ijccs.17838.
Wanto, A., & Windarto, A. P. (2017). Analisis Prediksi Indeks Harga Konsumen Berdasarkan Kelompok Kesehatan Dengan Menggunakan Metode Backpropagation. Jurnal & Penelitian Teknik Informatika Sinkron, 2(2), 37–43.
Downloads
Additional Files
Published
How to Cite
Issue
Section
License
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
Â

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.









