ANALISIS SENTIMEN DANA DAN GOPAY MENGGUNAKAN MODEL INDOBERT - Dalam bentuk pengganti sidang - Rancangan Karya Akhir
MUHAMMAD ALIF IMAM RAMADHAN

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Kode

25.04.5333

Klasifikasi

000 - General Works

Jenis

Karya Ilmiah - Skripsi (S1) - Reference

Subjek

Big Data

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157 kali

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Abstraksi

This study examines user sentiment toward the e-wallet applications DANA<br /> and GoPay, which are widely used today. The dataset comprised 10,000 reviews<br /> from Google Play Store and X for each platform between May 1 and June 1, 2025,<br /> of which 6,457 DANA reviews and 7,274 GoPay reviews remained after data<br /> cleaning. Sentiment classification using the IndoBERT model achieved average<br /> accuracies of 93 % for DANA and 88 % for GoPay, confirming the robustness of<br /> this approach. The analysis revealed a dominance of positive sentiment (37.4 % for<br /> GoPay and 34.7 % for DANA), followed by neutral (31.0 % and 32.6 %) and<br /> negative sentiment (31.6 % and 32.7 %), indicating substantial user satisfaction.<br /> Evaluation of E-Service Quality dimensions showed strengths in reliability (49.1 %<br /> for GoPay; 37.4 % for DANA) and responsiveness (38.0 % and 34.9 %), but<br /> highlighted critical weaknesses in site organization for GoPay (58.8 % negative)<br /> and in user friendliness (35.7 % negative) and personal needs (34.4 % negative)<br /> for DANA. Topic modeling further identified positive themes—responsive<br /> interfaces, transaction speed, promotions/cashback—as well as neutral-to-negative<br /> themes related to technical support requests, transaction failures, security<br /> concerns, and performance issues. These findings provide an empirical foundation<br /> for DANA and GoPay to devise targeted strategies to enhance UX/UI, system<br /> stability, and customer support, ultimately strengthening user satisfaction and<br /> loyalty.<br /> Keywords: Sentiment Analysis, DANA, GoPay, IndoBERT, Topic Modeling

• EBI3B4 - BIG DATA AND DATA ANALYTICS

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