Pengaruh Harga dan Kualitas Produk terhadap Keputusan Pembelian Motor Honda Beat pada PT. Sinar Sentosa Primatama Sungai Bahar Jambi - Robby Andre Inderwan (Universitas Batanghari Jambi, 2021)
With the development of the times, we are indirectly required to follow various existing developments. Human needs are not limited to make us think about how to solve this problem by meeting the various human needs. The design of this research is descriptive quantitative which aims to see the description of price and product quality on purchasing decisions, so that it can be seen the elements that are maintained and improved by PT. Sinar Sentosa Primatama and can improve its quality. The research variables are price and product quality on purchasing decisions. The research population is consumers who buy Honda Beat motorcycles at PT. Sinar Sentosa Primatama Sungai Bahar Muaro Jambi. The sampling method is random sampling. Samples were taken 73 people. The research instrument used a questionnaire containing 36 items. The research method is carried out using multiple linear regression analysis tools with the help of SPSS 22. The tests carried out are hypothesis testing, namely t test, f test and to find out how big the coefficient of determination (R2) is. Based on the results of this study, the price variable t count is smaller than t table with a value of (1.422 > 1.984), thus Ho is accepted and H1 is rejected, and the product quality variable t count is greater than t table with a value of (3,740 > 1,994), then H1 is accepted HO is rejected. The value of the coefficient of determination (R2) is 50.2%, which means that the contribution of the independent variables, namely price (X1) and product quality (X2) affects the dependent variable on purchasing decisions (Y) by 50.2%, while the remaining 49.8% is influenced by by other factors. So it can be concluded that the price and product quality have a significant effect on purchasing decisions at PT. Sinar Sentosa Primatama Sungai Bahar Muaro Jambi. The results of the multiple linear regression analysis are Y = 29,879 + 0,234 %3D X+ 0,353 X2