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All Journal Journal of Computer Science, Information Technology and Telecommunication Engineering (JCoSITTE)
Tri Andre Anu
Universitas Potensi Utama
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering

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Utilization of Digital Image and Convolution Neural Network Algorithm in Customer Satisfaction Survey with Facial Expressions Tri Andre Anu; Rika Rosnelly; Dedi Irawan; Progresif Bulolo; Ubaidullah Hasibuan
Journal of Computer Science, Information Technology and Telecommunication Engineering Vol 4, No 2 (2023)
Publisher : Universitas Muhammadiyah Sumatera Utara, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30596/jcositte.v4i2.15915

Abstract

The human face provides us with a lot of information about a person, and arguably the two most important pieces of information in a face are a person's identity and their emotional state. Judgments of identity and emotion facilitate social interactions. Services are a crucial part of the activities of all organizations, especially those in the service sector. Good services support customer satisfaction and ultimately impact the progress of the organization. The Convolutional Neural Network algorithm has become the most widely used neural architecture in various tasks, including image classification, audio pattern recognition, machine translation of text, and speech recognition. The data groups (angry, fearful, happy, neutral, sad, and surprised) tested with a threshold value of 30 epochs achieved a loss (error) accuracy of 1.5146 on the test data. The accuracy on the test data is 0.61. The proposed Convolutional Neural Network algorithm and digital image utilization achieved high accuracy performance to assist in evaluating a service-related field.
Co-Authors Dedi Irawan Progresif Bulolo Rika Rosnelly Ubaidullah Hasibuan