{"id":755,"date":"2026-01-22T14:11:50","date_gmt":"2026-01-22T14:11:50","guid":{"rendered":"https:\/\/rajawalimediautama.site\/?post_type=mbdb_book&#038;p=755"},"modified":"2026-02-05T07:25:22","modified_gmt":"2026-02-05T07:25:22","slug":"text-mining-untuk-analisis-sentimen-pendekatan-konvensional-hingga-aspect-based-sentimen-analysis","status":"publish","type":"mbdb_book","link":"https:\/\/rajawalimediautama.site\/?mbdb_book=text-mining-untuk-analisis-sentimen-pendekatan-konvensional-hingga-aspect-based-sentimen-analysis","title":{"rendered":"Text Mining Untuk Analisis Sentimen: Pendekatan Konvensional hingga Aspect-Based Sentimen Analysis"},"author":1,"comment_status":"open","ping_status":"closed","template":"","class_list":["post-755","mbdb_book","type-mbdb_book","status-publish","hentry","mbdb_genre-pendidikan","mbdb_genre-teknologi","mbdb_editor-nur-wahyu-hanani","mbdb_narrator-haeni-budiati","mbdb_narrator-hairani","mbdb_narrator-jatmika","mbdb_narrator-mariana-syamsudin","mbdb_narrator-sunneng-sandino-berutu","mbdb_narrator-victor-crisman-mendrofa","post"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v20.7 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Text Mining Untuk Analisis Sentimen: Pendekatan Konvensional hingga Aspect-Based Sentimen Analysis - Rajawali Media Utama<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/rajawalimediautama.site\/?mbdb_book=text-mining-untuk-analisis-sentimen-pendekatan-konvensional-hingga-aspect-based-sentimen-analysis\" \/>\n<meta property=\"og:locale\" content=\"id_ID\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Text Mining Untuk Analisis Sentimen: Pendekatan Konvensional hingga Aspect-Based Sentimen Analysis - Rajawali Media Utama\" \/>\n<meta property=\"og:description\" content=\"Buku Text Mining untuk Analisis Sentimen: Pendekatan Konvensional hingga Aspect-Based Sentiment Analysis hadir sebagai referensi komprehensif bagi mahasiswa, peneliti, praktisi, serta masyarakat umum yang ingin memahami teknik pengolahan data teks dan analisis opini secara mendalam. Pesatnya perkembangan teknologi digital menghasilkan data teks dari media sosial, e-commerce, layanan publik, dan berbagai platform daring yang menyimpan informasi penting tentang persepsi dan sentimen masyarakat. Buku ini disusun secara sistematis, dimulai dari konsep dasar text mining, pra-pemrosesan, dan representasi teks, hingga pendekatan analisis sentimen berbasis leksikon, machine learning, dan deep learning. Pembahasan kemudian berfokus pada keterbatasan analisis sentimen global serta memperkenalkan Aspect-Based Sentiment Analysis (ABSA) beserta pengembangannya seperti ASTE, ASOTE, dan structured sentiment analysis. Pada bagian akhir, disajikan panduan implementasi berbasis Python yang mencakup pipeline pemodelan, pelatihan, inferensi, serta evaluasi kinerja model.  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