ANALISIS SENTIMEN CUSTOMER REVIEW DI E-COMMERCE TOKOPEDIA MENGGUNAKAN METODE SUPPORT VECTOR MACHINE (SVM) DAN ADAPTIVE SYNTHETIC SAMPLING (ADASYN)

RIZKY, MUHAMMAD GANDA and Yusliani, Novi and Primanita, Anggina (2024) ANALISIS SENTIMEN CUSTOMER REVIEW DI E-COMMERCE TOKOPEDIA MENGGUNAKAN METODE SUPPORT VECTOR MACHINE (SVM) DAN ADAPTIVE SYNTHETIC SAMPLING (ADASYN). Undergraduate thesis, Sriwijaya University.

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Abstract

Sentiment analysis is the process of automatically understanding, extracting, and processing textual data to uncover information about opinions contained within the data, determining whether they are negative or positive. This study aims to perform sentiment analysis and evaluate the performance of algorithms in classifying customer reviews on the Indonesian e-commerce platform, Tokopedia, using the Support Vector Machine (SVM) algorithm and Adaptive Synthetic Sampling (ADASYN). The SVM algorithm was chosen for its ability to handle complex classification problems, while the ADASYN technique was employed to address the imbalance between the majority and minority classes in the dataset, which consists of 2,819 negative reviews and 450 positive reviews. The results show that the combination of the SVM and ADASYN algorithms have the highest accuracy with an accuracy rate of 93.7%, a recall of 76.6%, and an f1-score of 79%. Keywords : Adaptive Synthethic Sampling, algorithm, dataset, Sentiment analysis, Support Vector Machine.

Item Type:	Thesis (Undergraduate)
Uncontrolled Keywords:	Adaptive Synthethic Sampling, algorithm, dataset, Sentiment analysis, Support Vector Machine.
Subjects:	Q Science > Q Science (General) > Q334-342 Computer science. Artificial intelligence. Algorithms. Robotics. Automation.
Divisions:	09-Faculty of Computer Science > 55201-Informatics (S1)
Depositing User:	Muhammad Ganda Rizky
Date Deposited:	05 Jul 2024 04:00
Last Modified:	05 Jul 2024 04:00
URI:	http://repository.unsri.ac.id/id/eprint/149444

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