Rintyarna, Bagus Setya and Kuswanto, Heri and Sarno, Riyanarto and Rachmaningsih, Emy Kholifah and Suharso, Wiwik and Cahyanto, Triawan Adi (2022) (Similarity) Modelling Service Quality of Internet Service Providers during COVID-19: The Customer Perspective Based on Twitter Dataset. MDPI-Informatics.
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Abstract
Internet service providers (ISPs) conduct their business by providing Internet access features to their customers. The COVID-19 pandemic has shifted most activity being performed remotely using an Internet connection. As a result, the demand for Internet services increased by 50%. This significant rise in the appeal of Internet services needs to be overtaken by a notable increase in the service quality provided by ISPs. Service quality plays a great role for enterprises, including ISPs, in retaining consumer loyalty. Thus, modelling ISPs’ service quality is of great importance. Since a common technique to reveal service quality is a timely and costly pencil survey-based method, this work proposes a framework based on the Sentiment Analysis (SA) of the Twitter dataset to model service quality. The SA involves the majority voting of three machine learning algorithms namely Naïve Bayes, Multinomial Naïve Bayes and Bernoulli Naïve Bayes. Making use of Thaicon’s service quality metrics, this work proposes a formula to generate a rating of service quality accordingly. For the case studies, we examined two ISPs in Indonesia, i.e., By.U and MPWR. The framework successfully extracted the service quality rate of both ISPs, revealing that By.U is better in terms of service quality, as indicated by a service quality rate of 0.71. Meanwhile, MPWR outperforms By.U in terms of customer service.
| Item Type: | Peer Review |
|---|---|
| Uncontrolled Keywords: | ISPs; service quality; sentiment analysis |
| Subjects: | 600 Technology and Applied Science > 620 Engineering |
| Divisions: | Faculty of Engineering > Department of Electronics Engineering (S1) |
| Depositing User: | Bagus Setya Rintyarna |
| Date Deposited: | 23 Dec 2022 01:28 |
| Last Modified: | 24 Jan 2023 04:33 |
| URI: | http://repository.unmuhjember.ac.id/id/eprint/15682 |
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