Analisis Sentimen Ulasan Pengguna Aplikasi Mobile JKN di Google Play Store Menggunakan Algoritma K-Nearest Neighbors (KKN): Penelitian

Mario Marcelino; Vina Pratiwi; Naila Rahma; Dicky Apdillah

doi:10.31004/jerkin.v4i4.6720

Authors

Mario Marcelino
Vina Pratiwi
Naila Rahma
Dicky Apdillah

DOI:

https://doi.org/10.31004/jerkin.v4i4.6720

Keywords:

Analisis Sentimen; Mobile JKN, K-Nearest Neighbors (KNN), TF-IDF, Google Play Store.

Abstract

Perkembangan teknologi digital mendorong transformasi layanan kesehatan melalui aplikasi digital, salah satunya aplikasi Mobile JKN yang dikembangkan BPJS Kesehatan. Meningkatnya penggunaan aplikasi ini diikuti bertambahnya ulasan pengguna di Google Play Store yang dapat digunakan untuk mengetahui persepsi terhadap kualitas layanan. Penelitian ini bertujuan menganalisis sentimen ulasan pengguna Mobile JKN menggunakan algoritma K-Nearest Neighbors (KNN). Data diperoleh melalui web scraping sebanyak 1.000 ulasan. Tahapan penelitian meliputi pengumpulan data, pelabelan sentimen berdasarkan rating, preprocessing (cleaning, case folding, tokenization, stopword removal, dan stemming), ekstraksi fitur menggunakan TF-IDF, serta klasifikasi dengan KNN. Hasil menunjukkan sentimen positif mendominasi sebanyak 577 ulasan (57,7%), diikuti sentimen negatif 385 ulasan (38,5%), dan sentimen netral 38 ulasan (3,8%). Kata dominan pada sentimen positif adalah bagus, mudah, cepat, membantu, dan praktis, sedangkan sentimen negatif didominasi error, login, otp, gagal, dan lemot. Evaluasi model menunjukkan akurasi sebesar 87,59%, sehingga KNN efektif digunakan untuk klasifikasi sentimen ulasan Mobile JKN. Hasil penelitian ini diharapkan menjadi bahan evaluasi bagi pengembang untuk meningkatkan kualitas layanan dan pengalaman pengguna aplikasi Mobile JKN.

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