Improvement on I-Devices Using L-GCNN Classifier for Smart Mosque Simulation

Abstract I-Device (Intelligent Devices) is one of the fastest growing devices since beginning this decade. Some its major problems are accuracy and performance. This study aims to present an improvement in performance those devices. We used a simulation application for I-Devices conduct experiment. The was built based on classifying results using Logarithmic learning Generalized Classifier Neural Networks (L-GCNN). output that will be implemented smart mosque system. L-GCNN itself modification method GCNN improve processing speed have high as classifier method. take role when given parameters meet conditions action. To simplify understanding models, we game make interactive our project environment represents real-world condition mosque. result shows could decision by themselves accurately. Additionally, LGCNN reduce iteration compared other models. experiment show has average value 90% accuracy, precision, recall, f1. Keywords: Automation, Classifier, L-GCNN, Network, Decision.