Analisis Sentimen Berbasis Aspek pada Ulasan Aplikasi Gojek
DOI:
https://doi.org/10.24002/konstelasi.v4i1.8922Keywords:
Gojek, ulasan pengguna, sentimen, akurasi, Aspect Based Sentiment Analysis (ABSA)Abstract
Penggunaan aplikasi mobile meningkat pesat di era digital, termasuk Gojek, aplikasi populer di Indonesia yang menyediakan layanan transportasi, pesan antar makanan, dan pembayaran digital. Ulasan pengguna di Play Store menunjukkan berbagai masalah yang memerlukan perhatian. Ulasan ini memberikan wawasan tentang pandangan pengguna, memungkinkan identifikasi masalah, dan pengembangan layanan. Dengan teknik Aspect Based Sentiment Analysis (ABSA), pandangan pengguna dapat dipahami lebih baik, membantu evaluasi dan perbaikan aplikasi Gojek untuk meningkatkan kualitas layanan dan kepuasan pengguna. Penelitian ini bertujuan menganalisis sentimen berdasarkan aspek-aspek dalam ulasan pengguna aplikasi Gojek di Play Store dalam bahasa Inggris, dengan mencari pola sentimen yang akurat dan mengidentifikasi aspek yang perlu diperbaiki. Data diambil dari ulasan pengguna aplikasi Gojek di Google Play Store. Teknik pemodelan topik Latent Dirichlet Allocation (LDA) digunakan untuk mengidentifikasi topik-topik relevan. Pelabelan sentimen dilakukan menggunakan model BERT, sementara evaluasi sentimen dan aspek dilakukan dengan model distilbert-base-uncased-finetuned-sst-2-english. Hasil menunjukkan bahwa model BERT mencapai akurasi tertinggi untuk sentimen sebesar 96.67% dan aspek Service sebesar 98.78%. Terdapat ruang untuk perbaikan terutama pada aspek user experience, service, dan payment. Faktor-faktor yang mempengaruhi akurasi termasuk distribusi sentimen, jumlah data, preprocessing, dan model yang digunakan.
Mobile app usage is increasing rapidly in the digital era, including Gojek, a popular app in Indonesia that provides transportation, food delivery, and digital payment services. User reviews in the Play Store indicate various issues that require attention. These reviews provide insight into user views, enabling problem identification and service development. With the Aspect Based Sentiment Analysis (ABSA) technique, user views can be better understood, helping evaluate and improve the Gojek application to improve service quality and user satisfaction. This research aims to analyze sentiment based on aspects of user reviews of the Gojek application on the Play Store in English by finding accurate sentiment patterns and identifying aspects that need to be improved. The data was taken from user reviews of the Gojek application on the Google Play Store. Latent Dirichlet Allocation (LDA) topic modeling technique was used to identify relevant topics. Sentiment labeling was performed using the BERT model, while sentiment and aspect evaluation were performed with the distilbert-base-uncased-finetuned-sst-2-english model. The results showed that the BERT model achieves the highest accuracy for sentiment at 96.67% and Service aspects at 98.78%. There is room for improvement, especially in the user experience, service, and payment aspects. Factors affecting accuracy include sentiment distribution, amount of data, preprocessing, and the model used.
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