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      "abstract": "Fenomena judi online di Indonesia menunjukkan peningkatan yang\r\nsignifikan dan banyak bermunculan promosi terselubung di ruang publik digital,\r\nsehingga menimbulkan risiko sosial-ekonomi dan tantangan bagi upaya penegakan\r\nkebijakan. Penelitian ini bertujuan memetakan isu terkait judi online pada komentar\r\npublik YouTube dengan membandingkan dua pendekatan pemodelan topik: Latent\r\nDirichlet Allocation (LDA) dan Non-Negative Matrix Factorization (NMF). Data\r\ndikumpulkan melalui YouTube Data API v3 pada rentang 30 Agustus 2023–7\r\nDesember 2025 dan setelah validasi diperoleh 6.205 komentar top-level. Proses \r\nanalisis meliputi pra-pemrosesan teks (case folding, pembersihan URL\/emoji, \r\nnormalisasi slang, tokenisasi, stopword removal, stemming, dan pembentukan\r\nbigram), representasi BoW untuk LDA serta TF-IDF untuk NMF, pelatihan model\r\ndengan variasi jumlah topik, dan evaluasi menggunakan metrik koherensi serta\r\ninspeksi manual untuk interpretasi topik dan visualisasi temporal. Hasil\r\nmenunjukkan beberapa topik dominan seperti modus promosi (tautan\/afiliator),\r\nistilah permainan (slot, togel), mekanisme deposit\/withdraw, peran influencer, dan\r\nkritik publik terhadap dampak ekonomi; NMF cenderung menghasilkan topik yang\r\nlebih mudah diinterpretasi sementara LDA efektif menangkap campuran topik\r\ndalam komentar. Kontribusi penelitian meliputi pemetaan tematik isu judi online,\r\ndataset terstruktur untuk penelitian lanjutan, serta rekomendasi bagi pembuat\r\nkebijakan dan moderator platform untuk deteksi dan mitigasi konten. Rekomendasi\r\nlanjutan mencakup penerapan teknik embedding berbasis transformer dan\r\nperluasan sumber data lintas platform.",
      "title": "PEMETAAN ISU JUDI ONLINE DI INDONESIA MELALUI\r\nPEMODELAN TOPIK MENGGUNAKAN LDA DAN NMF",
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            "honourific": null,
            "family": "Baita"
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