TY - GEN
T1 - Sentiment Analysis of Service Quality of Online Healthcare Platform Using Fast Large-Margin
AU - Pandesenda, Adam Imansyah
AU - Yana, Rika Rizki
AU - Sukma, Eki Aidio
AU - Yahya, Arifnur
AU - Widharto, Punto
AU - Hidayanto, Achmad Nizar
N1 - Publisher Copyright:
© 2020 IEEE.
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2020/11/19
Y1 - 2020/11/19
N2 - Mobile technology is a tool by which healthcare users are assisted. Health information technology has the ability to enhance individual health outcomes and increase healthcare quality, allowing better independent health management. The implementation of information technology in healthcare, particularly the development of healthcare services based on mobile technology (m-health), has already changed healthcare delivery by making it more available and affordable across developing world. Alodokter is Indonesia's number one digital health firm, that has significantly changed the axis of Indonesian health services in providing easily understood, reliable, and available medical information to everyone. This research use Alodokter as our analysis to determine its service quality from customer review from Google Play Store that will be measured by using sentiment analysis. We use Fast Large-Margin as classification methodology and sentiment analysis to classify these following service dimensions: system quality, interaction quality, and information quality. The result of this research is system quality get the most review from customer and interaction quality get the most positive sentiment from customer review.
AB - Mobile technology is a tool by which healthcare users are assisted. Health information technology has the ability to enhance individual health outcomes and increase healthcare quality, allowing better independent health management. The implementation of information technology in healthcare, particularly the development of healthcare services based on mobile technology (m-health), has already changed healthcare delivery by making it more available and affordable across developing world. Alodokter is Indonesia's number one digital health firm, that has significantly changed the axis of Indonesian health services in providing easily understood, reliable, and available medical information to everyone. This research use Alodokter as our analysis to determine its service quality from customer review from Google Play Store that will be measured by using sentiment analysis. We use Fast Large-Margin as classification methodology and sentiment analysis to classify these following service dimensions: system quality, interaction quality, and information quality. The result of this research is system quality get the most review from customer and interaction quality get the most positive sentiment from customer review.
KW - alodokter
KW - Fast Large-Margin
KW - m-health
KW - sentiment analysis
KW - service quality
UR - http://www.scopus.com/inward/record.url?scp=85102168855&partnerID=8YFLogxK
U2 - 10.1109/ICIMCIS51567.2020.9354295
DO - 10.1109/ICIMCIS51567.2020.9354295
M3 - Conference contribution
AN - SCOPUS:85102168855
T3 - Proceedings - 2nd International Conference on Informatics, Multimedia, Cyber, and Information System, ICIMCIS 2020
SP - 121
EP - 125
BT - Proceedings - 2nd International Conference on Informatics, Multimedia, Cyber, and Information System, ICIMCIS 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2nd International Conference on Informatics, Multimedia, Cyber, and Information System, ICIMCIS 2020
Y2 - 19 November 2020 through 20 November 2020
ER -