Penerapan Data Mining Analisa Data Penjualan Obat Menggunakan Metode Random Forest
-
Cut Reka
*
Universitas Budi Darma, Medan,
Indonesia
(*) Corresponding Author
Abstract
Data Mining is a method used to find and explore certain hidden data from big data. For example, data mining can be used to find information on the combination of items in a sale. By using data mining, companies will be able to analyze precisely, quickly and accurately compared to analyzing manually. The pharmacy is one of the companies that can take advantage of this data mining method, because in the pharmacy sales transactions take place every day so that the longer the sales data stored is very large. Application of Data Mining sales data analysis Using the Random Forest Method in this method the data and attributes are taken at random so that it is possible to produce a decision tree model, the benefits of which are to facilitate the analysis of large data and help provide information on processed sales data.
Downloads
References
E. Buulolo, Data Mining Untuk Perguruan Tinggi. Deepublish, 2020.
D. Nofriansyah, Konsep Data Mining Vs Sistem Pendukung Keputusan. 2015.
H. Zhu, X. Xia, J. Yao, H. Fan, Q. Wang, and Q. Gao, “Comparisons of different classification algorithms while using text mining to screen psychiatric inpatients with suicidal behaviors,” J. Psychiatr. Res., vol. 124, no. December 2019, pp. 123–130, 2020.
W. Apriliah, I. Kurniawan, M. Baydhowi, and T. Haryati, “Prediksi Kemungkinan Diabetes pada Tahap Awal Menggunakan Algoritma Klasifikasi Random Forest,” Sistemasi, vol. 10, no. 1, p. 163, 2021.
A. Thakkar and R. Lohiya, “Attack classification using feature selection techniques: a comparative study,” J. Ambient Intell. Humaniz. Comput., vol. 12, no. 1, 2021.
Bila bermanfaat silahkan share artikel ini
Berikan Komentar Anda terhadap artikel Penerapan Data Mining Analisa Data Penjualan Obat Menggunakan Metode Random Forest
Pages: 114-117
Copyright (c) 2022 Cut Reka
This work is licensed under a Creative Commons Attribution 4.0 International 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 Creative Commons Attribution 4.0 International License that allows others to share the work with an acknowledgment 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 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 (Refer to The Effect of Open Access).
