PERHITUNGAN ESTIMASI WAKTU PADA PRODUKSI BARANG DENGAN MENERAPKAN ALGORITMA NAIVE BAYES KLASIFKASI (STUDI KASUS PT. HASIL RAYA INDUSTRIES)
DOI:
https://doi.org/10.31000/jika.v5i1.4126Abstract
PT. Hasil Raya Industries is a company engaged in the manufacture of plastic gods such as bottles of packaging. During this time there is difficulty in calculating the estimated duration of the product work. Because the calculation of estimation is still manual, not well recorded and not accurate. To support the estimation of production time, a web-based system is designed to solve the problem. The authors apply the Naive Bayes algorithm based on Data Demand Goods and Production Data Data at PT. Hasil Raya Industries to give solution in finding time estimation at work of goods production This application can run well and can produce information as expected. By using the application time of production of goods, PT.Hasil Raya Industries can directly receive reports of estimation results of production time.ÂÂ
Â
References
E. Manalu, F. A. Sianturi dan M. R. Manalu, “Penerapan Algoritma Naive Bayes Untuk Memprediksi Jumlah Produksi Barang Berdasarkan Data Persediaan dan Jumlah Pemesanan Pada CV. Papadan Mama Pastries,†vol. 1 No 2 Desember 2017, 2017.
Fatmawati, “Perbandingan Algoritma Klasifikasi Data Mining Model C4.5 dan Naivr Bayes untuk Prediksi Penyakit DIabetes,†Vol. %1 dari %2XIII, No. 1 Maret 2016, 2016.
L. Oktafiani dan H. D. Purnomo, “Model Forecasting Penjualan Sayuran Menggunakan Metode Naive Bayes (Studi Kasus: Jogja Organic, Yogyakarta),†2016.
L. Serovia dan S. Sudaryanto, “Prediksi Data Buku yang Sering Dipinjam Berdasarkan Kategori Pada Perpustakaan Daerah Dmak Menggunakan Metode Naive Bayes,†2016.
A. Saleh, “Implementasi Metode Klasifikasi Naive Bayes Dalam Memprediksi Besarnya Penggunaan Listrik Rumah Tangga,†Citec Journal, 2015.
S. M. Pratama, W. Kurniawan dan H. Fitriyah, “Implementasi Algoritme Naive Bayes Menggunakan Arduino Uno untuk Otomatisasi Lampu Ruangan Berdasarkan Kebiasaan dari Penghuni Rumah,†JPTIIK, vol. 2, no. 9, pp. 2485-2490, 2018.
R. R. Wijayanti, R. S. Septarini, S. M. Husain dan A. Abdurrasyid, “MODEL RUMAH PINTAR DENGAN MENGGUNAKAN LOGIKA FUZZY SEBAGAI PENGENDALI KEAMANAN DAN KESELAMATAN PENGHUNI RUMAH,†JANAPATI, vol. 9, no. 2, pp. 146-157, 2020.
S.Basuki, Pengantar Ilmu Perpustakaan, Jakarta: PT. Gramedia Pustaka Utama, 1991.
E. Prasetyo, Data Mining-Konsep dan Aplikasi menggunakan MATLAN, Yogyakarta: Andi, 2012.
Downloads
Published
Issue
Section
License
License and Copyright Agreement
In submitting the manuscript to the journal, the authors certify that:
- They are authorized by their co-authors to enter into these arrangements.
- That it is not under consideration for publication elsewhere,
- That its publication has been approved by all the author(s) and by the responsible authorities – tacitly or explicitly – of the institutes where the work has been carried out.
- They secure the right to reproduce any material that has already been published or copyrighted elsewhere.
- They agree to the following license and copyright agreement.
Copyright
Authors who publish with International Journal of Advances in Intelligent Informatics 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 (CC BY-SA 4.0) that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal.Â
- 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 acknowledgment 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.
Licensing for Data Publication
International Journal of Advances in Intelligent Informatics use a variety of waivers and licenses, that are specifically designed for and appropriate for the treatment of data:
Open Data Commons Attribution License, http://www.opendatacommons.org/licenses/by/1.0/ (default)
Creative Commons CC-Zero Waiver, http://creativecommons.org/publicdomain/zero/1.0/
Open Data Commons Public Domain Dedication and Licence, http://www.opendatacommons.org/licenses/pddl/1-0/
Other data publishing licenses may be allowed as exceptions (subject to approval by the editor on a case-by-case basis) and should be justified with a written statement from the author, which will be published with the article.
Open Data and Software Publishing and Sharing
The journal strives to maximize the replicability of the research published in it. Authors are thus required to share all data, code or protocols underlying the research reported in their articles. Exceptions are permitted but have to be justified in a written public statement accompanying the article.
Datasets and software should be deposited and permanently archived inappropriate, trusted, general, or domain-specific repositories (please consult http://service.re3data.org and/or software repositories such as GitHub, GitLab, Bioinformatics.org, or equivalent). The associated persistent identifiers (e.g. DOI, or others) of the dataset(s) must be included in the data or software resources section of the article. Reference(s) to datasets and software should also be included in the reference list of the article with DOIs (where available). Where no domain-specific data repository exists, authors should deposit their datasets in a general repository such as ZENODO, Dryad, Dataverse, or others.
Small data may also be published as data files or packages supplementary to a research article, however, the authors should prefer in all cases a deposition in data repositories.