Prediksi Tingkat Penjualan Sepeda Motor dengan Metode Rough Set

 (*)Eka Praja Wiyata Mandala Mail (Universitas Putra Indonesia YPTK, Padang, Indonesia)
 Dewi Eka Putri (Universitas Putra Indonesia YPTK, Padang, Indonesia)

(*) Corresponding Author

Submitted: June 9, 2021; Published: July 31, 2021

Abstract

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.

Keywords


Prediction; Sales; Motorcycles; Data Mining; Rough Set

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