Pemodelan Topik Opini Publik Terhadap Pelayanan Haji 2024 Menggunakan Latent Dirichlet Allocation (LDA) pada Data Twitter
DOI:
https://doi.org/10.26418/justin.v13i3.90696Keywords:
Haji, Twitter, Pemodelan Topik, LDAAbstract
Salah satu kewajiban umat muslim adalah melaksanakan ibadah haji. Indonesia, salah satu negara dengan jemaah haji terbanyak di dunia, terus berupaya meningkatkan mutu penyelenggaraan haji sebagaimana diamanatkan dalam Undang-Undang Nomor 8 Tahun 2019. Hasil Survei Kepuasan Jemaah Haji 2024 yang dilakukan BPS menunjukkan tingkat kepuasan sebesar 88.20 poin. Meskipun demikian, analisis kepuasan melalui media sosial menjadi penting karena memungkinkan masyarakat menyampaikan opini secara spontan dan terbuka, berbeda dengan survei tradisional yang memiliki batasan struktur dan respon. Media sosial terbukti menjadi sarana yang efektif untuk komunikasi dan koordinasi antara jemaah dan penyelenggara karena informasi disebarkan secara cepat dan langsung. Penelitian ini bertujuan untuk mengeksplorasi topik-topik utama yang dibicarakan terkait pelayanan haji Indonesia Tahun 2024 pada dataset sentimen positif, negatif, dan netral mengenai pelayanan haji 2024 menggunakan Latent Dirichlet Allocation (LDA) terhadap data Twitter. Hasil menunjukkan bahwa jumlah topik terbaik yang diklasifikasikan dalam analisis adalah 4 topik untuk sentimen negatif (coherence score 0.416) dan 5 topik untuk sentimen positif (0.475). Temuan ini memberikan gambaran rinci mengenai aspek pelayanan yang mendapat apresiasi maupun keluhan dari jemaah. Dengan demikian, hasil penelitian ini dapat digunakan sebagai masukan praktis oleh pemangku kebijakan, khususnya Kementerian Agama dan instansi terkait, untuk merumuskan perbaikan layanan haji yang lebih responsif terhadap kebutuhan dan pengalaman jemaah secara langsung.References
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