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      "keywords": "Topik berita, Sentimen, BERTopic, LDA, IDXFINANCE, News topic,Sentiment.",
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      "institution": "Universitas AMIKOM Yogyakarta",
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      "abstract": "Volume  berita  finansial  yang  masif  saat  ini  menjadikan  metode  analisis\r\n konvensional  kurang  efektif.  Kompleksitas  informasi  tersebut  menuntut\r\n pendekatan  big  data  untuk  memetakan  pola  dan  isu  pasar  secara  sistematis.\r\n Penelitian  ini  bertujuan  menganalisis  bagaimana  topik  dan  sentimen  berita  pasar\r\n finansial  Indonesia  merefleksikan  narasi  risiko  dan  peluang  di  sektor  keuangan.\r\n Metode  yang  digunakan  meliputi  pemodelan  topik  dengan  Latent  Dirichlet\r\n Allocation  (LDA)  dan  BERTopic,  serta  analisis  sentimen  pada  korpus  berita\r\n finansial.  Studi  ini  membandingkan  kinerja  kedua  model  dalam  aspek  koherensi\r\n topik,  serta  menguji  korelasi  antara  dinamika  topik-sentimen  dengan  pergerakan\r\n Indeks  Sektoral  Keuangan  (IDXFINANCE).  Hasil  penelitian  menunjukkan  bahwa\r\n BERTopic  mengungguli  LDA  dalam  menghasilkan  topik  yang  lebih  koheren  dan\r\n kontekstual.  Integrasi  analisis  topik  dan  sentimen  terbukti  efektif  dalam\r\n mengidentifikasi  narasi  pasar,  di  mana  dinamika  sentimen  memiliki  korelasi  yang \r\n signifikan  dengan  pergerakan  IDXFINANCE.  Temuan  ini  memberikan  wawasan \r\n terstruktur  bagi  investor,  analis,  dan  regulator  mengenai  isu-isu  penggerak  pasar.\r\n Penelitian  selanjutnya  disarankan  untuk  memperluas  cakupan  data  dan\r\n menerapkan pendekatan kausalitas untuk mendalami arah pengaruh antar variabel.",
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