{"title":"Word Cloud Result of Mobile Payment User Review in Indonesia","authors":"Intan Novita Dewi, R. Nurcahyo, Farizal","doi":"10.1109/ICIEA49774.2020.9102048","DOIUrl":null,"url":null,"abstract":"The volume of non-cash transaction grow rapidly all around the world. One of the global growth figures for noncash transactions is driven by the use of mobile payment. In 2018, Indonesia is proven to be a good market for mobile payment and estimated to continue to grow in 2020. This will make competition between mobile payment tougher in Indonesia. Mobile payment companies need to maintain the quality of services and applications in order to meet customer satisfaction. User reviews or complaints expressed on Twitter were used in this study. Pre-processing data is used to convert unstructured and semi-structured text into an understandable format. The Term Frequency matrix is used to calculate the number of occurrences of the token. Word cloud is used to represent the most repeated words that represent the word size. It can be used to find out what services are widely reviewed or complained by customers. The data in this study are tweets with Bahasa Indonesia therefore, the result for word cloud is also in Bahasa Indonesia. The eight frequently used words in the data can be grouped into mobile payment company, monetary rewards, mobile payment transaction and customer service.","PeriodicalId":306461,"journal":{"name":"2020 IEEE 7th International Conference on Industrial Engineering and Applications (ICIEA)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE 7th International Conference on Industrial Engineering and Applications (ICIEA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIEA49774.2020.9102048","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
The volume of non-cash transaction grow rapidly all around the world. One of the global growth figures for noncash transactions is driven by the use of mobile payment. In 2018, Indonesia is proven to be a good market for mobile payment and estimated to continue to grow in 2020. This will make competition between mobile payment tougher in Indonesia. Mobile payment companies need to maintain the quality of services and applications in order to meet customer satisfaction. User reviews or complaints expressed on Twitter were used in this study. Pre-processing data is used to convert unstructured and semi-structured text into an understandable format. The Term Frequency matrix is used to calculate the number of occurrences of the token. Word cloud is used to represent the most repeated words that represent the word size. It can be used to find out what services are widely reviewed or complained by customers. The data in this study are tweets with Bahasa Indonesia therefore, the result for word cloud is also in Bahasa Indonesia. The eight frequently used words in the data can be grouped into mobile payment company, monetary rewards, mobile payment transaction and customer service.