Penerapan Algoritma C4.5 Untuk Memprediksi Penjualan Lele Pada Kolam Pancing Galatama
Abstract
Advances in technology and information today can produce a smart innovation in business, which we can call business intelligence. In this technological advancement is the use of previous data which will later be used to obtain a data update to increase sales of a product in this case the technique is called a data mining technique which can extract useful information from the sales data warehouse. The use of data mining techniques is expected to help speed up the decision-making process,enabling decision-makers to manage the information contained in transaction data into new knowledge. Therefore the seller must be more careful in providing the type of product, in this case the researcher conducts research on the sale of catfish which will be in great demand, so that the seller will be able to provide recommendations for the type of catfish that has the most demand, so that the seller can classify types of catfish from the type, price, and weight of the catfish using aclassification method carried out using the C4.5 data mining algorithm. The C4.5 algorithm is a tree data type decision classification algorithm. The decision tree C4.5 algorithm is built in several stages which include selecting the attribute as the root, creating a branch for each value and dividing the case on the branch. This step will be repeated for each branch until all cases in the branch have the same class. From the results of tree testing of decision search results from sales datausing the RapidMiner Studio application, the results that have the highest gain in predicting catfish sales are weight and type so that it will produce the status of selling catfish in demand and those that are not selling by giving a value of >= 25 in katakana in demand. and <25 are said to be not selling well, so the Galatama pond manager can make a reference to pay attention to these two variables in selling catfish to get the best sales.
Keywords
Full Text:
PDFReferences
S. H. Bernadetha Aurelia Oktavira, “Apakah Sistem Pemancingan Galatama Termasuk Judi?,†Hukum Online, 2020. https://www.hukumonline.com/klinik/a/apakah-sistem-pemancingan-galatama-termasuk-judi-lt5df4402e47855 (accessed Jul. 04, 2022).
Y. Siska, “Penerapan Data Mining Dengan Algoritma Naive Bayes Pelanggan Terhadap Pelayanan Servis Mobil ( Studi Kasus : Katamso Service ),†Maj. Ilm. INTI, vol. 6, 2019.
D. Wanto, Anjar, Data Mining : Algoritma dan Implementasi - Books. 2020.
R. D. Endarwati and S. Hermuningsih, “Pengaruh Struktur Modal Dan Pertumbuhan Penjualan terhadap Nilai Perusahaan dengan Profitabilitas Sebagai Variabel Intervening Pada Perusahaan Property Dan Real Estate Yang Terdaftar Di Bursa Efek Indonesia Tahun 2013-2017,†SEGMEN J. Manaj. Dan Bisnis, vol. 15, no. 1, pp. 63–70, 2019.
Dwi Retnosari, “Sistem Aplikasi Data Mining Untuk Menampilkan,†J. Integr. Sist. Ind. UMJ, vol. 1, no. 2, pp. 13–20, 2014.
A. F. Tanjung, T. M. Diansyah, and R. Rismayanti, “Pemanfaatan Algortima K-Means Clustering Sebagai Pengamanan Pencurian Buah Kelapa Sawit Se-Distrik Tandun PT. Perkebunan Nusantara V,†J. MEDIA Inform. BUDIDARMA, vol. 3, no. 4, 2019, doi: 10.30865/mib.v3i4.1443.
H. Widayu, S. Darma, N. Silalahi, and Mesran, “Data Mining Untuk Memprediksi Jenis Transaksi Nasabah Pada Koperasi Simpan Pinjam Dengan Algoritma C4.5,†Issn 2548-8368, vol. Vol 1, No, no. June, 2017.
M. B. Islamia, A. Riyadi, and S. Oyama, “Data Mining Pemesanan Bibit Ikan Menggunakan Metode Least Square (Studi Kasus: UPTD-BBI Barongan Jetis Kabupaten Bantul Provinsi Yogyakarta),†Seri Pros. Semin. Nas. Din. …, pp. 62–65, 2021.
D. Sartika and Yupianti, “Klasifikasi Penyakit Tiroid Menggunakan Algoritma C4 . 5,†J. Sci. Technol., vol. 13, no. 1, 2020.
K. Kunci, K. I. P. Kartu, I. Pintar, D. Mining, and D. Tree, “Penerapan Metode Data Mining C4 . 5 Untuk Pemilihan Penerima Kartu Indonesia Pintar ( KIP ),†vol. 23, no. 2, 2021.
K. de Groot, “No 主観的å¥åº·æ„Ÿã‚’ä¸å¿ƒã¨ã—ãŸåœ¨å®…高齢者ã«ãŠã‘ã‚‹ å¥åº·é–¢é€£æŒ‡æ¨™ã«é–¢ã™ã‚‹å…±åˆ†æ•£æ§‹é€ 分æžTitle,†World Dev., vol. 1, no. 1, pp. 1–15, 2018, [Online]. Available: http://www.fao.org/3/I8739EN/i8739en.pdf%0Ahttp://dx.doi.org/10.1016/j.adolescence.2017.01.003%0Ahttp://dx.doi.org/10.1016/j.childyouth.2011.10.007%0Ahttps://www.tandfonline.com/doi/full/10.1080/23288604.2016.1224023%0Ahttp://pjx.sagepub.com/lookup/doi/10.
E. E. Oktaviastuti, “Analisis Perilaku Konsumen dalam Membeli Ikan Lele di Pasar Tradisional Kabupaten Boyolali,†2011, [Online]. Available: https://digilib.uns.ac.id/dokumen/detail/20944/Analisis-Perilaku-Konsumen-dalam-Membeli-Ikan-Lele-di-Pasar-Tradisional-Kabupaten-Boyolali.
M. Firmansyah and R. Aufany, “Implementasi Metode Decision Tree Dan Algoritma C4.5 Untuk Klasifikasi Data Nasabah Bank,†Infokam, vol. XII, no. 1, pp. 1–12, 2016.
DOI: https://doi.org/10.30865/json.v3i4.4264
Refbacks
- There are currently no refbacks.
Copyright (c) 2022 Tengku Mohd Diansyah, Yogi Exprada

This work is licensed under a Creative Commons Attribution 4.0 International License.
Jurnal Sistem Komputer dan Informatika (JSON)
Dikelola oleh Universitas Budi Darma
Sekretariat : Jln. Sisingamangaraja No. 338 Telp 061-7875998
email : jurnal.json@gmail.com

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