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      "uri": "http:\/\/eprints.amikom.ac.id\/id\/eprint\/32382",
      "keywords": "Analisis sentimen, Mobile Legends: Bang Bang Professional League, \r\nSupport Vector Machine (SVM), Komentar Youtube, Confision Matrix, Synthetic\r\nMinority Over-sampling Technique (SMOTE), Sentyment analysis.",
      "thesis_type": "bachelor",
      "date_type": "published",
      "status_changed": "2026-07-27 04:47:26",
      "ispublished": "pub",
      "type": "thesis",
      "department": "Fakultas Ilmu Komputer",
      "date": "2026-02-25",
      "rev_number": 21,
      "subjects": [
        "000.000.005",
        "700.790.794"
      ],
      "creators": [
        {
          "nim": "19.11.3212",
          "name": {
            "lineage": null,
            "given": "Yohan Wahid",
            "family": "Sub'han",
            "honourific": null
          }
        }
      ],
      "dir": "disk0\/00\/03\/23\/82",
      "abstract": "Perkembangan teknologi informasi dan komunikasi mendorong \r\nmeningkatnya penggunaan media digital, khususnya media sosial seperti Youtube,\r\nsebagai sarana masyarakat untuk menyampaikan opini dan pandangan. Banyaknya\r\nkomentar yang dihasilkan pada platform tersebut bepotensi menjadi sumber data\r\nuntuk mengetahui sentimen masyarakat, termasuk dalam bidang e-sports.\r\nPenelitian ini bertujuan untuk melakukan analisis sentimen terhadap tim terfavorit\r\npada ajang Mobile Legends: Bang Bang Professional League (MPL) di Indomesia\r\nberdasarkan komentar pengguna Youtube menggunakan metode Support Vector\r\nMachine (SVM). Data yang digunakan diperoleh dari komentar Youtube pada kanal\r\nresmi MPL Indonesia yang berkaitan dengan pertandingan dan tim-tim peserta.\r\nTahapan penelitian meliputi pengumpulan data, pra-pemrosesan teks, pembobotan\r\nkata Term Frequency-Inverse Document Frequency (TF-IDF), serta proses\r\nklasifikasi sentimen ke dalam kelas positif dan negatif menggunakan metode SVM.\r\nPengujian model dilakukan dengan membagi data ke dalam data latih dan data uji.\r\nHasil penelitian menunjukkan bahwa metode SVM mampu mengklasifikasikan\r\nsentimen komentar Youtube dengan tingkat akurasi yang baik, sehingga dapat\r\ndigunakan untuk mengidentifikasi persepsi dan antusiasme masyarakat tehadap tim\r\nterfavorit dalam kompetisi MPL Indonesia.",
      "title": "ANALISIS SENTIMEN TIM TERFAVORIT MOBILE\r\nLEGENDS: BANG BANG PROFESSIONAL LIGA DI \r\nINDONESIA BERDASARKAN KOMENTAR YOUTUBE\r\nMENGGUNAKAN METODE SUPPORT VECTOR MACHINE",
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          "name": {
            "given": "Heri",
            "lineage": null,
            "family": "Sismoro",
            "honourific": null
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