Sentiment Analysis of Transportation Application Reviews with SVM on Handling Imbalanced Data Using SMOTE - Dalam bentuk buku karya ilmiah

DIAH AYU LESTARI

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68 kali
25.04.530
000
Karya Ilmiah - Skripsi (S1) - Reference

Transportation has become an inseparable element of Indonesian society. In April 2024, the number of motor vehicles in Indonesia reached 161,787,250 units, causing traffic congestion in various regions, especially in large cities. The Mitra Darat application, as one of the transportation company applications, was initially known as "Teman Bus." This application has evolved into a multi-service platform such as BRT Nusantara, KSPN, and Perintis. This study analyzes sentiment toward reviews of transportation company applications to improve public transportation services in Indonesia. Sentiment analysis has been carefully conducted on user reviews in the Google Play Store using the Support Vector Machine (SVM) technique. The imbalanced data was addressed using the SMOTE and SMOTE-ENN techniques. The model was evaluated using accuracy, precision, recall, and F1-Score metrics. The results show that the accuracy achieved by the Support Vec

Subjek

Machine Learning
 

Katalog

Sentiment Analysis of Transportation Application Reviews with SVM on Handling Imbalanced Data Using SMOTE - Dalam bentuk buku karya ilmiah
 
v, 8p.: il,; pdf file
English

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Pengarang

DIAH AYU LESTARI
Perorangan
Yuliant Sibaroni, Sri Suryani Prasetyowati
 

Penerbit

Universitas Telkom, S1 Informatika
Bandung
2025

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