Consumers will make purchasing decisions about a product influenced by several things, namely, price and consumers can make purchasing decisions. This is the company's main goal in making a profit. Apart from price, what influences purchasing decisions is brand image, where brand image plays an important role in a decision to purchase a Vivo cellphone. The formulation of the problem in this research is 1. Does price influence the decision to purchase Vivo cellphones at Griya Satria Cibeber Housing, 2. Does brand image influence the decision to purchase Vivo cellphones at Griya Satria Cibeber Housing, 3. Do price and brand image influence purchasing decisions Vivo cellphone at Griya Satria Cibeber Housing Complex. This research aims to find out how influential price and brand image are on purchasing decisions for Vivo cellphones. The analysis method used is quantitative descriptive analysis and uses a survey method of 60 respondents. The data collection technique uses an instrument in the form of a questionnaire. Data analysis uses classical assumption tests, multiple linear regression and coefficient of determination analysis. Based on the results of the hypothesis test, the value tcount > ttable (3,455 > 2,542) and the significant value 0.001 < ? (0.05), then H0 is rejected and Ha is accepted. Based on the significance test, it was found that there is a significant influence between the price variable (X1) on purchasing decisions (Y). And the value of tcount > ttable (4,593 > 2,542) and the significant value is 0.000 < ? (0.05), then H0 is rejected and Ha is accepted. Based on the significance test, it was found that there is a significant influence between the brand image variable (X2) on purchasing decisions (Y).
 
 

Peningkatan pertumbuhan penduduk di Semarang berbanding lurus dengan peningkatan kebutuhan sampah dan listrik. Persoalannya, sampah hanya berpindah dari tempat pembuangan sampah ke tempat pembuangan akhir. Hal ini menyebabkan munculnya dampak buruk terhadap lingkungan kota yang kotor. Di sisi lain, permintaan kebutuhan listrik yang tinggi setiap tahunnya meningkat. Untuk mengatasi masalah ini adalah pemborosan telah dimanfaatkan bahan pembangkit listrik. Dua parameter telah diusulkan untuk memprediksi potensi pembangkit listrik tenaga sampah di kota Semarang seperti populasi dan sampah. Algoritma backpropagation dari JST telah digunakan untuk memprediksi pembangkit listrik tenaga sampah untuk tahun 2020 hingga 2022. Variabel yang digunakan dalam peramalan meliputi ukuran populasi dan volume sampah. Hasil penelitian menunjukkan bahwa produksi listrik WPP adalah 8,8 MWH untuk peramalan 3 tahun. sedangkan pertumbuhan orang ditunjukkan sebagai 1,7 juta selama 3 tahun. Potensi pembangkit listrik sampah PLN telah diberikan 0,29% dari total kebutuhan listrik di Jawa Tengah.