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Image of Implementation of aspect-based sentiment analysis on the Mitra Darat App user reviews using machine learning

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Implementation of aspect-based sentiment analysis on the Mitra Darat App user reviews using machine learning

Maulaya Ishaq - Nama Orang - Pengarang Utama; Dewi Lestari - Nama Orang - Pembimbing; Michael Marchenko - Nama Orang - Pembimbing;

The Mitra Darat application is an Android-based application available on the Google Play Store, developed try the Directorate General of Land Transportation (Ministry of Transportation). User reviews on this platform enable direct communication with developers, offering valuable feedback for service enhancement and future development. For that reason, aspect-hased sentiment analysis is needed to help organizations monitor product sentiment in user feedback, and understand user needs. This research aims implement aspect-based sentiment analysis on Mitra Darut application user reviews to gemerate insights via a system dashboard Comparing Naive Bayes (NII) and Support Vector Machines (SVM) for machine learning models with the addition of pre Indobert as word embedding, SVM showed superior performance with an accuracy score of 94% for aspect classification and 90% for sentiment classification, compared to Naive Hayes with scores of 64% and 78% respectively The trained Support Vector Machine model (SVM) was then utilized to analyze 967 reviews of the Mitra Darat application for 2023. The results of the analysis are presenmod on a dashboard page with summary information, which shows the overall user sentiment is 52.3% positive, 10% neutral, and 377 negative. In terms of sentiment polarity by aspect, the system aspect is 29% positive, 8% neutral, and 63% negative, meaning that wome bugs and usues have been found in the application, so it can be evaluated for future system development. The service aspects 62% positive, 27% neutral, and 11% negative, which means that the free mudik service is quite well organined.


Ketersediaan
TI24/019TI 24/019Prodi Teknik Informatika (Ruang Skripsi dan Tesis)Tersedia
Informasi Detail
Judul Seri
-
No. Panggil
TI 24/019
Penerbit
Jakarta : Universitas Trilogi., 2024
Deskripsi Fisik
-
Bahasa
English
ISBN/ISSN
-
Klasifikasi
TI
Tipe Isi
text
Tipe Media
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Tipe Pembawa
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Edisi
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Subjek
Information technology
Trilogi University--Information technology
Info Detail Spesifik
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Pernyataan Tanggungjawab
Maulaya Ishaq
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