TY - GEN
T1 - Analysis on customer satisfaction dimensions in peer-to-peer accommodation using latent dirichlet allocation
T2 - 5th International Conference on Electrical Engineering Computer Science and Informatics, EECSI 2018
AU - Situmorang, Kevin M.
AU - Hidayanto, Achmad N.
AU - Wicaksono, Alfan F.
AU - Yuliawati, Arlisa
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/10/1
Y1 - 2018/10/1
N2 - Customer satisfaction becomes a key influencer for people’s habits or daily activities. One of the examples is in the decision-making process about whether they will use specific products or services. People often need other’s review or rating about what they are going to use or consume. In this research, by using customer’s online review that available from Airbnb website, we try to extract what are the most talked factors about peer-to-peer accommodation, and how customer sentiment about them. We use Latent Dirichlet Allocation (LDA) to extract that factors and conduct sentiment analysis by utilizing semantic analyzer from Google Cloud NLP. We analyze which factors that has more effect on customer satisfaction, not only in general but more specific based on customer gender and tourism destination object. The result shows that factors related to social benefit and service quality have impact on customer satisfaction, moreover different customer gender and different tourism object destination bring different sentiment among customer. We also find several factors that can be improved by the owner of the accommodation to improve customer satisfaction toward their services.
AB - Customer satisfaction becomes a key influencer for people’s habits or daily activities. One of the examples is in the decision-making process about whether they will use specific products or services. People often need other’s review or rating about what they are going to use or consume. In this research, by using customer’s online review that available from Airbnb website, we try to extract what are the most talked factors about peer-to-peer accommodation, and how customer sentiment about them. We use Latent Dirichlet Allocation (LDA) to extract that factors and conduct sentiment analysis by utilizing semantic analyzer from Google Cloud NLP. We analyze which factors that has more effect on customer satisfaction, not only in general but more specific based on customer gender and tourism destination object. The result shows that factors related to social benefit and service quality have impact on customer satisfaction, moreover different customer gender and different tourism object destination bring different sentiment among customer. We also find several factors that can be improved by the owner of the accommodation to improve customer satisfaction toward their services.
KW - Customer Satisfaction
KW - Latent Dirichlet Allocation
KW - Peer-to-Peer Accommodation
KW - Sentiment Analysis
UR - http://www.scopus.com/inward/record.url?scp=85069217851&partnerID=8YFLogxK
U2 - 10.1109/EECSI.2018.8752912
DO - 10.1109/EECSI.2018.8752912
M3 - Conference contribution
AN - SCOPUS:85069217851
T3 - International Conference on Electrical Engineering, Computer Science and Informatics (EECSI)
SP - 542
EP - 547
BT - Proceedings - 2018 5th International Conference on Electrical Engineering Computer Science and Informatics, EECSI 2018
A2 - Stiawan, Deris
A2 - Subroto, Imam Much Ibnu
A2 - Riyadi, Munawar A.
A2 - Aditya, Christian Sri Kusuma
A2 - Has, Zulfatman
A2 - Yudhana, Anton
A2 - Minarno, Agus Eko
PB - Institute of Advanced Engineering and Science (IAES)
Y2 - 16 October 2018 through 18 October 2018
ER -