ANALISIS OPINI PENGGUNA APLIKASI SHOPEE DENGAN NAÃVE BAYES CLASSIFIER

Penulis

DOI:

https://doi.org/10.31000/jika.v9i3.14462

Abstrak

Pertumbuhan pesantnya e-commerce di Indonesia berdampak pada meningkatnya ulasan pengguna terhadap aplikasi belanja berani seperti Shopee. Ulasan ini mewakili persepsi pengguna dan dapat dimanfaatkan untuk memancarkan kepuasan serta meningkatkan kualitas layanan. Menggunakan algoritma Naive Bayes, studi ini menerapkan strategi klasifikasi untuk memahami sikap dalam ulasan pengguna aplikasi shopee di Google Play Store. Data diperoleh menggunakan teknik web scraping dan kemudian menjalani beberapa proses, termasuk pembersihan data teks, tokenisasi, penghapusan kata-kata yang tidak relevan, dan normalisasi. Sentimen evaluasi dirinci secara manual ke dalam tiga kelompok berbeda: sangat_puas, puas, dan tidak_puas. Untuk mengatasi distribusi kelas, digunakan teknik RandomOverSampler Sebelum data dibagi menjadi set pelatihan dan pengujian, teks kemudian dianalisis menggunakan teknik TF-IDF dan dibor dengan algoritma Multinomial Naive Bayes. Akurasi, presisi, recall, skor F1, dan matriks kebingungan dimasukkan ke dalam proses evaluasi untuk menyalakan kinerja model. Hasil penelitian menunjukkan bahwa model memperoleh tingkat ketepatan mencapai 75,33% dengan kinerja yang cukup konsisten di semua label. Teknik oversampling terbukti efektif dalam menyeimbangkan kelas, meskipun masih terdapat prediksi silang antar kategori yang mirip. Penelitian ini menjadi pijakan awal bagi pengembangan sistem analisis sentimen otomatis berbasis bahasa Indonesia.

Referensi

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2025-07-31

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Vol 9 No 3 (2025): JIKA (Jurnal Informatika)

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