Jurnal AKSI (Akuntansi dan Sistem Informasi)
Vol 5, No 2 (2020)

Implementation of Deep Learning for Slump Optimization Based on Concrete Quality Using Convolutional Neural Network in PT. SELO PROGO SAKTI

Pandowo, Hedi (Unknown)



Article Info

Publish Date
16 Sep 2020

Abstract

Deep Learning is part of the scientific field of Machine Learning and Machine Learning is part of Artificial Intelligence science. Deep Learning has extraordinary capabilities by using a hardware Graphical Processing Unit (GPU) so that the artificial requirement network can run faster than using a Personal Computer Unit (CPU). Especially in terms of object classification in images using existing methods in the Convolutional Neural Network (CNN). The method used in this research is Preprocessing and Processing of Input Data, Training Process in which CNN is trained to obtain high accuracy from the classification carried out and the Testing Process which is a classification process using weights and bias from the results of the training process. This type of research is a pre experimental design (pre experimental design). The results of the object image classification test with different levels of confusion in the Concrete database with the Mix Design K-125, K-150, K-250 and K-300 produce an average accuracy value. This is also relevant to measuring the failure rate of concrete or slump

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Journal Info

Abbrev

aksi

Publisher

Subject

Computer Science & IT Economics, Econometrics & Finance

Description

Jurnal AKSI (Akuntansi dan Sistem Informasi) with registered number ISSN 2541-3198 (printed), ISSN 2541-6145 (online) is scientific journals which publish articles from the fields of accounting and information system. AKSI will publish in two times issues Volume 1, Numbered: 1-2 are scheduled for ...