Prediksi Penjualan Mobil dalam Negeri sebagai Penentu Kebijakan Pengelolaan Kompetensi Keahlian Teknik Kendaraan Ringan (TKR) di Sekolah Menengah Kejuruan (SMK)
Abstract
Sales of four-wheeled vehicles in the domestic market at the beginning of 2021 experienced a decline on a monthly and annual basis as a result of the Covid-19 pandemic. This has caused the wheels of the economy not to turn normally as a result of social restrictions. Therefore, this study was conducted to analyze and predict the increase in sales of four-wheeled vehicles using machine learning algorithms. This study uses literature studies using journals about prediction models. To obtain the appropriate algorithm, a comparison of the test results of the journals used is carried out. This prediction of domestic car sales is used to make policies for managing the competence of Light Vehicle Engineering (TKR) expertise at SMK. The results of this study produced a prediction model with the best performance, namely SARIMA with an MSE value of 0.89 and a Backpropagation Artificial Neural Network with an MSE value of 0.44
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