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      "department": "Fakultas Ilmu Komputer",
      "title": "ANALISIS SENTIMEN UMPAN BALIK MAHASISWA\r\nTERHADAP DOSEN MENGGUNAKAN NAÏVE BAYES",
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      "contributors": [
        {
          "name": {
            "given": "Rizqi Sukma",
            "lineage": null,
            "honourific": null,
            "family": "Kharisma"
          }
        }
      ],
      "rev_number": 15,
      "creators": [
        {
          "name": {
            "given": "Irenius Putra",
            "honourific": null,
            "family": "Agung",
            "lineage": null
          },
          "nim": "22.11.5119"
        }
      ],
      "date": "2026-04-08",
      "corp_creators": [
        "Universitas AMIKOM Yogyakarta"
      ],
      "keywords": "analisis sentimen, naïve bayes, TF-IDF, sentiment scoring, umpan\r\nbalik mahasiswa, sentiment analysis, sentiment scoring, student\r\nfeedback.",
      "date_type": "published",
      "dir": "disk0\/00\/03\/30\/88",
      "abstract": "Perkembangan teknologi informasi di era digital menyebabkan peningkatan\r\njumlah data, termasuk data umpan balik mahasiswa terhadap dosen yang umumnya\r\nberbentuk teks tidak terstruktur. Permasalahan yang muncul adalah sulitnya\r\nmenganalisis data tersebut secara manual karena jumlahnya yang besar, sehingga\r\nberpotensi menghambat proses evaluasi kualitas pengajaran. Penelitian ini\r\nbertujuan untuk menganalisis sentimen umpan balik mahasiswa terhadap dosen\r\nmenggunakan algoritma Naïve Bayes yang dipadukan dengan sentiment scoring.\r\nMetode yang digunakan meliputi tahapan preprocessing teks, ekstraksi fitur\r\nmenggunakan TF-IDF, pembagian data menjadi training dan testing dengan rasio\r\n80:20, pelatihan model Naïve Bayes, evaluasi menggunakan confusion matrix, serta\r\npenerapan sentiment scoring untuk mengukur intensitas sentimen. Hasil penelitian\r\nmenunjukkan bahwa model memiliki performa yang baik dengan akurasi sebesar\r\n83,18%, precision 82,25%, recall 97,42%, dan F1-score 89,19%. Selain itu,\r\ndiperoleh rata-rata skor sentimen sebesar 0,69 yang menunjukkan tingkat kepuasan\r\nmahasiswa terhadap dosen cenderung tinggi. Penelitian ini memberikan kontribusi\r\ndalam menghasilkan metode evaluasi kinerja dosen yang lebih objektif, terukur,\r\ndan berbasis data, serta dapat dimanfaatkan oleh institusi pendidikan untuk\r\nmeningkatkan kualitas pembelajaran. Penelitian selanjutnya disarankan untuk\r\nmengembangkan metode dengan algoritma lain atau dataset yang lebih beragam."
    }