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          "name": {
            "given": "Septiano Dwiyanto",
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      "title": "ANALISIS SENTIMEN PENGGUNA MOBILE LEGENDS DI\r\nTWITTER MENGGUNAKAN ALGORITMA NAÏVE BAYES",
      "institution": "Universitas AMIKOM Yogyakarta",
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      "rev_number": 15,
      "date": "2026-01-20",
      "uri": "http:\/\/eprints.amikom.ac.id\/id\/eprint\/32076",
      "abstract": "Perkembangan game online, khususnya Mobile Legends: Bang Bang, \r\nmemunculkan beragam opini dari penggunanya di media sosial. Twitter menjadi\r\nsalah satu platform yang banyak digunakan untuk menyampaikan tanggapan\r\nterhadap game tersebut, sehingga berpotensi menjadi sumber data untuk\r\nmenganalisis persepsi publik.\r\nPenelitian ini bertujuan untuk menganalisis sentimen pengguna terhadap\r\ngame Mobile Legends berdasarkan data tweet menggunakan algoritma Naïve Bayes\r\nClassifier. Data dikumpulkan melalui proses crawling tweet, kemudian dilakukan\r\ntext preprocessing yang meliputi cleaning, tokenisasi, penghapusan stopword, dan\r\nstemming. Selanjutnya, data dilabeli ke dalam tiga kelas sentimen, yaitu positif,\r\nnegatif, dan netral, diekstraksi menggunakan metode TF-IDF, serta diklasifikasikan\r\nmenggunakan algoritma Naïve Bayes. Evaluasi model dilakukan menggunakan\r\nconfusion matrix dan metrik akurasi.\r\nHasil penelitian menunjukkan bahwa dari 5.716 data tweet yang dianalisis,\r\ndengan 3440 data bernilai netral, 643 data bernilai negatif dan 17633 data bernilai\r\npositif. Model Naïve Bayes menunjukkan kinerja yang cukup baik dengan nilai\r\nakurasi sebesar 83,38%, sehingga mampu mengklasifikasikan sentimen pengguna\r\ndengan cukup akurat.  \r\nPenelitian ini diharapkan dapat memberikan kontribusi dalam bidang\r\nanalisis sentimen dan klasifikasi teks berbahasa Indonesia, serta menjadi referensi\r\nbagi pengembang game, analis media sosial, dan peneliti dalam memahami persepsi\r\npengguna dan mengembangkan sistem pemantauan opini publik secara otomatis.",
      "type": "thesis",
      "thesis_name": "skripsi",
      "thesis_type": "bachelor",
      "keywords": "Analisis Sentimen, Mobile Legends, Twitter, Naïve Bayes, Klasifikasi\r\nTeks, sentiment analysis, text\r\nclassification.",
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            "family": "Pristyanto",
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            "honourific": null,
            "given": "Yoga"
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