Taufiqqurrahman, Husain (2023) PERBANDINGAN METODE ANALISIS SENTIMEN ULASAN APLIKASI MYPERTAMINA DENGAN MENGGUNAKAN ALGORITMA NAÏVE BAYES DAN K-NEAREST NEIGHBOR. Undergraduate thesis, UNIVERSITAS PEMBANGUNAN NASIONAL "VETERAN" JAWA TIMUR.
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Abstract
Reviews given by users on the Google Play Store platform play an important role in influencing opinions and assessments of applications in the ever-evolving digital era. Sentiment analysis of user reviews has an important role in understanding user sentiment and thoughts about the MyPertamina application. Departing from these problems, research in this final project will try to get a summary of data related to MyPertamina application user reviews and apply two Naïve Bayes and K-Nearest Neighbor classification algorithms to find out how appropriate each algorithm is in classifying Indonesian text related to MyPertamina application user reviews. The review dataset tested is divided into three sentiment labels, namely negative, neutral, and positive with the number of datasets used as much as 1500 review data scrapped from the Google Play Store. From the test results, the Naïve Bayes algorithm is superior with an accuracy rate of 76%, 75%, 73%. While the K-Nearest Neighbor algorithm has an accuracy rate of 72%, 66%, 65%, 60%, 56%, 73%, 68%, 65%, 62%, 59%, 69%, 64%, 62%, 59%, 58%.
| Item Type: | Thesis (Undergraduate) | ||||||||||||
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| Subjects: | T Technology > T Technology (General) | ||||||||||||
| Divisions: | Faculty of Computer Science > Departemen of Informatics | ||||||||||||
| Depositing User: | Husain Taufiqqurrahman | ||||||||||||
| Date Deposited: | 21 Nov 2023 03:13 | ||||||||||||
| Last Modified: | 21 Nov 2023 03:13 | ||||||||||||
| URI: | http://repository.upnjatim.ac.id/id/eprint/18722 |
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