Applied Technology and Computing Science Journal
Vol 2 No 2 (2019): December

Performance Evaluation of Integrated Deep Learning Web Platform for Dataset Training

Sritrusta Sukaridhoto (Politeknik Elektronika Negeri Surabaya)
Dwi Kurnia Basuki (Politeknik Elektronika Negeri Indonesia)
Heri Yulianus (Simpul Technologies)
Rizqi Putri Nourma Budiarti (Universitas Nahdlatul Ulama Surabaya)



Article Info

Publish Date
31 Mar 2020

Abstract

Along with the complexity of recent web site, many users cannot get the benefits. We developed Integrated Deep Learning Web Platform to help researcher to prepare dataset trainig for Tensorflow. However, the quality of a web site needs to be assessed. This paper proposes an implementation of WebQual 4.0 for evaluating Integrated Deep Learning Platform for Training Dataset (INDEF) quality. This method used the WebQual model that has some instruments. The instruments grouped the WebQual questions to be three main categories; usability, information and service interaction. From the research conducted can be evaluated that all respondents agreed Integrated Deep Learning Platform for Training Dataset web site met all the WebQual characteristics.

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Journal Info

Abbrev

ATCSJ

Publisher

Subject

Engineering Social Sciences

Description

Applied Technology and Computing Science Journal ( ISSN 2621-4458, E-ISSN 2621-4474) is a journal on all aspect of applied technology natural science that published online by Faculty of Engineering – University of Nahdlatul Ulama Surabaya. This journal published periodically twice in a year (on ...