RANCANGAN SISTEM REKOMENDASI PEMILIHAN JENIS SMARTPHONE DENGAN METODE JARINGAN SYARAF TIRUAN - Ilham Ramadhani, - (2019)
Newley Purnell announced that this increase also discusses the protection of consumers in Southeast Asia who prefer smart phone products at varying prices with high-end features such as camera features, design, and battery and storage capacity. In this study, using backpropagtion artificial nerves is expected to provide another alternative in estimating and predicting the level of smartphone purchases. From the results of the study, the best network architecture was obtained from the 4-10-4-5 network pattern architecture and the best training algorithm. Artificial Neural Network backpropagation method for rating system in smartphone selection has a high level of accuracy which produces 85.52% and which the system cannot read by 14.48%. Such as gender, age, type of work, salary and so on