TOPSIS in Decision-Making Framework Based on Twitter Sentiment Analysis

ERNA, DANIATI and Hastari, Utama (2021) TOPSIS in Decision-Making Framework Based on Twitter Sentiment Analysis. In: 2021 4rd International Conference on Information and Communications Technology (ICOIACT, 30-31 Agustus 2021, Online.

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Twitter is one of social media that categorized in microblogging. Tweets on Twitter which are short sentences containing an opinion or sentiment. This is very beneficial for the organization or company to conduct analysis. The objective for this analysis is market prediction, general elections, measuring reactions to events or news, and measuring subjectivity. This affects the decision making for the company. Therefore, the role of sentiment analysis is very necessary to get the classification of sentiment in the form of positive, negative, and neutral sentiments. This type of sentiment polarity is used as a criteria for preference modeling so that alternative decisions can be calculated for the final value. This study attempts to propose a decision-making framework based on sentiment analysis. In addition, this research is also an improvement from the previous decision-making framework where decision-making is based on sentiment analysis. Improvements were made to the modeling of the criteria which initially used the SAW method to be changed to the TOPSIS method. Furthermore, the final value of the decision alternatives using TOPSIS is compared with using SAW. The comparison parameters used are in the form of final scores and ranking results. The final score of the SAW method is greater than the TOPSIS end score. In addition, there are differences in the ranking results between the TOPSIS and SAW methods.

Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: TOPSIS, SAW, DSS, Sentiment Analysis, Framewok
Subjects: 410 Engineering science > 461 Information systems
Divisions: Fakultas Teknik > S1-Sistem Informasi
Depositing User: Erna Daniati
Date Deposited: 28 Apr 2022 00:03
Last Modified: 28 Apr 2022 00:03

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