ANALISIS SENTIMEN PENGGUNAAN BUS DAMRI DI KOTA PALEMBANG MENGGUNAKAN METODE K-NEAREST NEIGHBORS

SAYMONA, YONA and Fathoni, Fathoni (2022) ANALISIS SENTIMEN PENGGUNAAN BUS DAMRI DI KOTA PALEMBANG MENGGUNAKAN METODE K-NEAREST NEIGHBORS. Undergraduate thesis, Sriwijaya University.

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Abstract

Sentiment analysis or opinion mining is an analysis that aims to see the sentiment of the community or group regarding certain entities Currently the dissemination of information is very easy, by using a social media, users can share information with the general public. As an example of information or opinions regarding the performance of Damri itself in providing public transportation services to improve the quality and competitiveness of the transfortation business competition and the fluctuations in the decline in the number of passengers which is a topic to be used by the public in providing opinions. Many assumptions of responses are expressed by the community through social media such as Twitter, such as positive responses or negative responses, such as regarding the services and facilities provided by damri in serving the community. In addition to pulling data through crawling data on tweet data, researchers also disseminated questionnaires. In carrying out the sentiment analysis classification process, it can be done using methods such as, then the researcher wants to conduct research on community sentiment analysis on the Damri Bus using the K-nearest Neighbors method. The results of this study are testing and training data on 1768 data records producing the highest accuracy with a value of K = 5 which has an accuracy of 88.12%.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Sentiment Analysis, K-Nearest Neighbor, Damri Bus, Twitter.
Subjects:	T Technology > T Technology (General) > T1-995 Technology (General)
Divisions:	09-Faculty of Computer Science > 57201-Information Systems (S1)
Depositing User:	Yona Saymona
Date Deposited:	20 Sep 2022 03:07
Last Modified:	20 Sep 2022 03:07
URI:	http://repository.unsri.ac.id/id/eprint/79146

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