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      "abstract": "Perkembangan industri permainan berbasis perangkat mobile mendorong meningkatnya\r\njumlah pengguna serta ulasan yang diberikan pada platform distribusi aplikasi, seperti Google\r\nPlay Store. Ulasan tersebut mengandung opini pengguna mengenai kualitas permainan,\r\nperforma aplikasi, serta tingkat kepuasan secara umum. Penelitian ini bertujuan untuk\r\nmenganalisis sentimen masyarakat terhadap permainan World of Airports berdasarkan ulasan\r\npengguna yang diperoleh dari Google Play Store. \r\nSecara garis besar, alur penelitian ini terdiri dari serangkaian proses yang saling \r\nberkesinambungan. Tahap awal dimulai dengan pengumpulan data pengguna yang diperoleh \r\ndari Google Play Store melalui proses web crawling. Setelah data terkumpul, dilakukan \r\ntahapan preprocessing teks yang meliputi case folding, pembersihan karakter, tokenisasi, \r\npenghapusan stopwords, dan stemming untuk membersihkan data. Langkah selanjutnya adalah \r\nekstraksi fitur menggunakan metode Term Frequency–Inverse Document Frequency (TF-IDF). \r\nGuna mengatasi masalah ketidakseimbangan kelas pada data, penelitian ini menerapkan \r\nmetode Synthetic Minority Over-sampling Technique (SMOTE). Pada tahap akhir, proses \r\nklasifikasi sentimen dijalankan menggunakan algoritma Support Vector Machine (SVM). \r\nHasil pengujian menunjukkan bahwa model yang dibangun mampu mengklasifikasikan \r\nsentimen dengan tingkat akurasi sebesar 89%.",
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