Prediksi Tingkat Penjualan Sepeda Motor dengan Metode Rough Set
DOI:
https://doi.org/10.30865/mib.v5i3.3057Keywords:
Prediction, Sales, Motorcycles, Data Mining, Rough SetAbstract
The high level of motorcycle sales makes the showroom have difficulty in procuring variants of motorcycles to be sold. The many variants of motorcycles in one manufacturer, make different sales of each motorcycle variant, there are variants with high sales and some with low sales. So it is necessary to predict the level of motorcycle sales. This study uses data from one of the Honda motorcycle showrooms, namely the Hayati showroom, Pasaman branch. The data used is a recapitulation of motorcycle sales data in the second quarter of 2020. This study uses 24 data samples as a decision system. From the test results obtained 13 equivalence classes, then a reduction process is carried out to obtain 7 reducts and a rules generation process is carried out, then 41 rules are obtained with Motorcycle Prices as the dominant attribute in influencing the Sales Level attribute decisions with an incidence of 42% and min. support = 5.References
L. Sinaga, A. Ahmad, and M. Safii, “Implementasi Data Mining Menggunakan Algoritma Apriori Pada Penjualan Sepeda Motor Jenis Honda (Studi Kasus : Showroom Honda Arista Pematangsiantar),†MEANS (Media Inf. Anal. dan Sist., vol. 5, no. 1, pp. 18–21, 2020.
S. Mulyani, D. Hayati, and A. N. Sari, “Analisis Metode Peramalan (Forecasting) Penjualan Sepeda Motor Honda Dalam Menyusun Anggaran Penjualan Pada PT Trio Motor Martadinata Banjarmasin,†Din. Ekon., vol. 14, no. 1, pp. 178–188, 2021.
Zulrahmadi, S. Defit, and Y. Yunus, “Pemetaan Wilayah Potensial Terhadap Penjualan Sepeda Motor Honda Menggunakan K-Means Clustering,†J. Inform. Ekon. Bisnis, vol. 2, pp. 53–59, 2020.
S. P. Sari, M. K. Sari, and L. D. Dahen, “Pengaruh Kualitas Produk, Sikap Konsumen Dan Kepercayaan Konsumen Terhadap Keputusan Pembelian Sepeda Motor Honda Beat Di CV. Hayati Cabang Pasaman Barat (Studi Kasus Di Kecamatan Pasaman Kabupaten Pasaman Barat),†Economica, vol. 5, no. 2, pp. 167–178, 2017.
R. Solin, N. I. Syahputri, and A. Budiman, “Metode Least Sequare Dalam Memprediksi Penjualan Sepeda Motor Second,†Semin. Nas. Teknol. Inf. dan Komun. 2020, vol. 969747907, no. 2020, pp. 372–381, 2020.
U. Indriani, “Penerapan Metode Rough Set Dalam Menentukan Pembelian Smartphone Android Oleh Konsumen,†J. Tek. Inform. Kamputama, vol. 2, no. 1, pp. 85–92, 2018.
D. E. Putri and E. P. W. Mandala, “Implementasi Algoritma FP-Growth Untuk Menemukan Pola Frekuensi Pembelian Lauk Pada Rumah Makan Takana Juo,†Media Inform. Budidarma, vol. 5, no. 1, pp. 242–250, 2021.
M. R. Raharjo and A. P. Windarto, “Penerapan Machine Learning dengan Konsep Data Mining Rough Set ( Prediksi Tingkat Pemahaman Mahasiswa terhadap Matakuliah ),†J. Media Inform. Budidarma, vol. 5, pp. 317–326, 2021.
R. A. Putra and S. Defit, “Data Mining Menggunakan Rough Set dalam Menganalisa Modal Upah Produksi pada Industri Seragam Sekolah,†J. Sistim Inf. dan Teknol., vol. 1, no. 4, pp. 72–78, 2019.
R. Tasya, E. Buulolo, and P. G. M, “Prediksi Kebohongan Manusia Melalui Wajah Dan Gerak Tubuh Menggunakan Metode Rough Set (Studi Kasus Polda Sumut),†Maj. Ilm. INTI, vol. 5, no. 3, pp. 227–231, 2018.
L. Lei, W. Chen, B. Wu, C. Chen, and W. Liu, “A building energy consumption prediction model based on rough set theory and deep learning algorithms,†Energy Build., vol. 240, p. 110886, 2021.
R. Daeli, “Analisa Pola Pegadaian Bpkb Sepeda Motor Dengan Menggunakan Metode Rough Set ( Studi Kasus : PT . GPS Finance Medan ),†J. Inf. dan Teknol. Ilm., vol. 7, no. 3, pp. 279–286, 2020.
H. Kurniawan, F. Agustin, Yusfrizal, and K. Ummi, “Implementation Data Mining in Prediction of Sales Chips with Rough Set Method,†2018 6th Int. Conf. Cyber IT Serv. Manag. CITSM 2018, no. Citsm, pp. 1–7, 2019.
M. A. Rahman, “Penerapan Metode Rough Set Dalam Memprediksi Penjualan Perumahan (Studi Kasus Di PT. Anugerah Pasadena Pekanbaru),†J. War. Dharmawangsa, vol. 14, no. 2, pp. 342–355, 2020.
Rasim, E. Junaeti, and R. Wirantika, “Implementation of Automatic Clustering Algorithm and Fuzzy Time Series in Motorcycle Sales Forecasting,†IOP Conf. Ser. Mater. Sci. Eng., vol. 288, no. 1, 2018.
P. Y. Saputra, I. D. Wijaya, and S. M. Anshori, “Sistem Peramalan Penjualan Sepeda Motor Yamaha Di Sentral Yamaha Malang Dengan Metode Least Square,†J. Aghinya Stiesnu Bengkulu, vol. 3, no. 2, 2020.
S. F. Utami, S. Y. Arisma, K. Hermanto, and E. Ruskartina, “Peramalan Jumlah Penjualan Sepeda Motor Menggunakan Metode Time Series Studi Kasus : Dealer Motor Nusantara Surya Sakti (NSS) Sumbawa,†Hexagon, vol. 1, no. 2, pp. 33–41, 2020.
M. Fajar and I. Gunawan, “Penerapan Jaringan Syaraf Tiruan Dengan Metode Backpropagation Untuk Memprediksi Penjualan Sepeda Motor Yamaha Di Asli Motor Siantar,†KLIK Kaji. Ilm. Inform. dan Komput., vol. 1, no. 4, pp. 180–186, 2021.
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