Analisis Sentimen terkait Penerapan E-Parking Ponorogo (Parkir-Go) dengan Metode Bidirectional Encoder from Transformers (BERT)
DOI:
https://doi.org/10.26418/justin.v13i2.86993Keywords:
BERT, Analisis Sentimen, Text MiningAbstract
Penelitian ini menganalisis sentimen masyarakat terhadap implementasi e-parking di Ponorogo menggunakan Bidirectional Encoder Representations from Transformers (BERT). Data dikumpulkan dari media sosial dan diklasifikasikan ke dalam sentimen negatif, netral, dan positif. Hasil awal menunjukkan bahwa model BERT kurang mampu mengenali sentimen positif, dengan akurasi awal hanya 50%. Setelah penerjemahan data ke dalam bahasa Indonesia dan Inggris, akurasi meningkat menjadi 55%, namun masih terdapat kesulitan dalam mengklasifikasikan sentimen netral dan positif. Dengan data augmentation melalui back translation, jumlah data bertambah menjadi 1.608, menghasilkan peningkatan akurasi sebesar 75% pada percobaan pertama dan 98% pada percobaan kedua. Dari analisis sentimen, ditemukan bahwa 42% komentar bersentimen negatif, didominasi oleh kekhawatiran tenaga parkir terhadap kesulitan adaptasi teknologi; 35% komentar bersentimen netral, menunjukkan kebingungan masyarakat terkait metode pembayaran; dan 23% komentar bersentimen positif, mengapresiasi transparansi tarif dan modernisasi layanan. Implikasi praktis dari hasil ini menunjukkan bahwa efektivitas e-parking dapat ditingkatkan melalui sosialisasi lebih intensif kepada masyarakat, pelatihan khusus bagi juru parkir, serta penyediaan opsi pembayaran yang lebih variatif. Selain itu, peningkatan infrastruktur dan pengoptimalan layanan teknis diperlukan untuk memastikan adopsi e-parking yang lebih luas dan berkelanjutan.
Kata kunci: Analisis Sentimen, BERT, E-Parking, Media Sosial , Ponorogo
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