Improvement on I-Devices using L-GCNN classifier for smart mosque simulation

Fadila, Juniardi Nur ORCID: https://orcid.org/0000-0002-5965-9243, Hariyadi, M. Amin, Hanani, Ajib, Prakasa, Johan Ericka Wahyu ORCID: https://orcid.org/0000-0001-5571-9328 and Aziz, Okta Qomaruddin (2022) Improvement on I-Devices using L-GCNN classifier for smart mosque simulation. International Journal of Advances in Soft Computing and its Applications, 14 (03). pp. 138-152. ISSN 2074-8523

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Abstract

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

Item Type:	Journal Article
Keywords:	automation; classifier; L-GCNN; neural network; decision
Subjects:	08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080108 Neural, Evolutionary and Fuzzy Computation 19 STUDIES IN CREATIVE ARTS AND WRITING > 1902 Film, Television and Digital Media > 190202 Computer Gaming and Animation 08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing
Divisions:	Faculty of Technology > Department of Informatics Engineering
Depositing User:	M.T. Juniardi Nur Fadila
Date Deposited:	01 Dec 2022 14:23

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