Data Mining menggunakan Metode Rough Set dalam Memprediksi Tingkat Penjualan Peralatan Komputer
|
Keywords:
Data Mining, Rough Set, Prediction, Sales, Computer Equipment
AbstractData mining is a job in the form of collecting and using data to get a rule, pattern, or relationship in large data. The output of this data mining can be used to facilitate future decision-making. The purpose of this study is to predict the level of sales of computer equipment to make it easier for sellers to meet consumer needs. The data processed in this study include several factors which will later be included in the Roughtset method. The method used is a Rough set. Factors include the name of goods, warranty, price, and level of sales. These factors will later be grouped in the Equivalence Class, where the same attribute values will be grouped. Then proceed to the next stage, namely the Discernibility Matrix which contains a collection of condition attributes that have different condition values. After that, proceed to the Discernibility Matrix Modulo D stage where the columns in the matrix are filled with a collection of condition attributes that have different conditions and different decision values. The next stage is Reduction, which is how to get the condition attributes used to get output in the form of knowledge. The last stage is knowledge which is the result of the reduction obtained. Then the results of the rough set application will be entered into the Rosetta application. The results obtained using the rough set method on 10 samples of computer equipment sales data, obtained 17 new rules or knowledge that can be used as guidelines in decision making to identify the level of computer sales. Downloads
Download data is not yet available.
References
Sofiyan, A., & Azkiya, A. (2022). Penerapan Metode Rough Set Menganalisis Penyakit yang Sering Dikeluhkan Pasien (Studi Kasus Puskesmas Jaya Mukti Dumai). Informatika, 14(1), 31-40. DOI: http://dx.doi.org/10.36723/juri.v14i1.348
Kurniawansyah, A. S. (2021). Penerapan Algoritma Rough Set Dalam Memprediksi Hasil Ujian Kompetensi Kebidanan. JSAI (Journal Scientific and Applied Informatics), 4(2), 135–140. DOI : https://doi.org/10.36085/jsai.v4i2.1504 Raharjo, M. R., & Windarto, A. P. (2021). Penerapan Machine Learning dengan Konsep Data Mining Rough Set (Prediksi Tingkat Pemahaman Mahasiswa terhadap Matakuliah). Jurnal Media Informatika Budidarma, 5(1), 317. DOI : https://doi.org/10.30865/mib.v5i1.2745 Hasanah, A. A., & Yunianti, D. N. (2021). Sifat-Sifat Himpunan Lunak. MATHunesa: Jurnal Ilmiah Matematika, 9(2), 311-321. DOI: https://doi.org/10.26740/mathunesa.v9n2.p311-321 Rahman, M. A. (2020). Penerapan Metode Rough Set dalam Memprediksi Penjualan Perumahan (Studi Kasus di PT. Anugrah Pasadena Pekanbaru). Fakultas Teknik Dan Ilmu Komputer, 14(2), 342–355. DOI: https://doi.org/10.46576/wdw.v14i2.632 Sugiraharjo, S., & Santi, R. C. N. (2021). TOPSIS dan Double Exponential Smoothing untuk Perangkingan dan Peramalan Penjualan Laptop. Jurnal Informatika Upgris, 7(1). DOI: https://doi.org/10.26877/jiu.v7i1.8341 Novianti, S., & Hasugian, P. M. (2021). Implementasi Algoritma Rough Set Untuk Memprediksi Jumlah Pendaftar Siswa Baru Pada SMK Swasta Sinar Harapan. Jurnal Teknik Informatika UNIKA Santo Thomas, 248-259. DOI: https://doi.org/10.54367/jtiust.v6i2.1433 Mandala, E. P. W., & Putri, D. E. (2021). Prediksi Tingkat Penjualan Sepeda Motor dengan Metode Rough Set. Jurnal Media Informatika Budidarma, 5(3), 896-904. DOI: http://dx.doi.org/10.30865/mib.v5i3.3057 Chaves, L., & Marques, G. (2021). Data mining techniques for early diagnosis of diabetes: a comparative study. Applied Sciences, 11(5), 2218. DOI : https://doi.org/10.3390/app11052218. Yendrizal, Y. (2020). Data Mining Penjualan Tanaman Hias dengan Algoritma Apriori Pada Toko Flores Elishabet. Jurnal Media Informatika Budidarma, 4(2), 472. DOI : https://doi.org/10.30865/mib.v4i2.2110 Panggabean, D. S. O., Buulolo, E., & Silalahi, N. (2020). Penerapan Data Mining Untuk Memprediksi Pemesanan Bibit Pohon Dengan Regresi Linear Berganda. Jurikom (Jurnal Riset Komputer), 7(1), 56-62. DOI: http://dx.doi.org/10.30865/jurikom.v7i1.1947 Li, H., Sun, H., Fan, F., Liu, H., Li, L., & Yin, F. (2022). Research on an intelligent disassembling method for multi-type mobile phones based on rough set theory. Procedia CIRP, 105, 547-552. DOI : https://doi.org/10.1016/j.procir.2022.02.091 |
Published
2022-12-31
Section
Articles
How to Cite
Zuhdi, I. (2022). Data Mining menggunakan Metode Rough Set dalam Memprediksi Tingkat Penjualan Peralatan Komputer. Jurnal Informatika Ekonomi Bisnis, 4(4), 142-147. https://doi.org/10.37034/infeb.v4i4.159
 This work is licensed under a Creative Commons Attribution 4.0 International License. |
