MULTILABEL ASPECT-BASED SENTIMENT ANALYSIS PADA DATA ULASAN MULTIBAHASA APLIKASI FLO PERIOD TRACKER MENGGUNAKAN MULTILINGUAL BERT DAN BERTOPIC

AFFAH, RIFDA NASYWATUL (2026) MULTILABEL ASPECT-BASED SENTIMENT ANALYSIS PADA DATA ULASAN MULTIBAHASA APLIKASI FLO PERIOD TRACKER MENGGUNAKAN MULTILINGUAL BERT DAN BERTOPIC. Undergraduate thesis, UPN "Veteran" Jawa Timur.

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Abstract

The development of the FemTech industry has increased the use of women's health applications such as Flo Period Tracker. Even though it has a high rating, there are still negative reviews that show dissatisfaction with certain aspects. This study aims to apply Aspect-Based Sentiment Analysis (ABSA) to multilingual reviews to identify aspects and sentiment trends. Aspect extraction was performed using BERTopic and resulted in six main aspects, including user experience, cycle tracking accuracy, app subscription, app usefulness, data management, and cycle period changes. Sentiment classification was performed using Multilingual BERT (mBERT) into three categories: positive, negative, and neutral. The experiment involved variations in data splitting (70:30, 80:20, 90:10), batch size (16 and 32), and data imbalance handling methods in the form of Cross Entropy Loss, Focal Loss, and Random Oversampling combined with Balanced Bagging Classifier (ROS BBC). The best results were obtained in the ROS BBC scenario with a 70:30 split and a batch size of 16 because it was able to provide balanced and more stable performance in handling minority classes, with an accuracy of 0.87, precision of 0.64, recall of 0.72, f1-score of 0.67, and AUC of 0.93. The model was then implemented in a web-based system for automatic aspect-based sentiment analysis.

Item Type: Thesis (Undergraduate)
Contributors:
ContributionContributorsNIDN/NIDKEmail
Thesis advisorWahyuni, Eka DyarNIDN0001128406ekawahyuni.si@upnjatim.ac.id
Thesis advisorSugata, Tri Luhur IndayantiNIDN8948770671230422tri.luhur.fasilkom@upnjatim.ac.id
Subjects: Q Science > Q Science (General)
Q Science > QA Mathematics > QA76.6 Computer Programming
T Technology > T Technology (General)
Divisions: Faculty of Computer Science > Departemen of Information Systems
Depositing User: Rifda Nasywatul
Date Deposited: 06 Mar 2026 03:48
Last Modified: 06 Mar 2026 07:21
URI: https://repository.upnjatim.ac.id/id/eprint/50192

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