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      "abstract": "Penelitian ini bertujuan mengembangkan sistem koreksi pelafalan bahasa Indonesia untuk anak usia dini dengan memanfaatkan teknologi Automatic Speech Recognition (ASR) dan Word Embedding FastText. Sistem dibangun menggunakan Faster-Whisper untuk mengubah suara menjadi teks, Word Embedding FastText untuk merepresentasikan kata dalam bentuk vektor numerik, serta Cosine Similarity untuk menghitung tingkat kemiripan antara hasil transkripsi dan kosakata target. Selain itu, sistem dilengkapi dengan fitur identifikasi jenis kesalahan pelafalan, rekomendasi stimulasi pengucapan, serta keluaran audio pelafalan yang benar menggunakan Google Text-to-Speech (TTS). Sistem diimplementasikan dalam bentuk aplikasi berbasis web yang memungkinkan pengguna mengunggah atau merekam suara secara langsung. Pengujian dilakukan melalui pengujian fungsional, pengujian performa, dan user testing. Hasil pengujian fungsional menunjukkan bahwa seluruh fitur sistem berjalan sesuai dengan rancangan yang telah ditetapkan. Pada pengujian performa, sistem memperoleh tingkat akurasi sebesar 89,80%, dengan 44 data berhasil dikoreksi sesuai kata target dari total 49 data uji. Sementara itu, hasil user testing yang melibatkan 3 orang guru TKIT Ulul Albab memperoleh nilai sebesar 87,62% dengan kategori Sangat Baik. Hasil penelitian menunjukkan bahwa kombinasi Faster-Whisper, Word Embedding FastText, dan Cosine Similarity mampu digunakan untuk mendukung proses koreksi pelafalan bahasa Indonesia secara otomatis serta memberikan umpan balik yang membantu latihan pengucapan anak usia dini.",
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      "referencetext": "Alfath, I., Fathony, N., Mareta, A., Adiana, B. E., Wardhani, O., Halim, A., Studi, P., & Informasi, T. (2025). ELKOM (Jurnal Elektronika dan Komputer) Optimisasi Whisper Speech-to-Text Bahasa Indonesia dengan Hybrid Cloud dan Multi-Engine. 18(1). https:\/\/doi.org\/10.51903\/5n2d3s08\r\nAnggraini, N., Bahasa, B., & Selatan, S. (2020). PERANAN ORANG TUA DALAM PERKEMBANGAN BAHASA ANAK USIA DINI. In METAFORA (Vol. 7).\r\nComputer Engineering Departement. (n.d.). Komputika: Jurnal Sistem Komputer. Komputika : Jurnal Sistem Komputer.\r\nHenry, H., & Eryc, E. (2024). Speech Recognition Untuk Membantu Pelafalan Hanyu Pinyin Sebagai Bagian Dari Edukasi Bahasa Mandarin. Jurnal Ilmiah Edutic : Pendidikan Dan Informatika, 10(2), 117–128. https:\/\/doi.org\/10.21107\/edutic.v10i2.22633\r\nInsani, H. (2024). Strategi Efektif untuk Meningkatkan Keterampilan Berbahasa pada Anak Usia Dini Pemalu Melalui Pendekatan Teori Zona Perkembangan Proksimal (ZPD) Vygotsky. Jurnal Pendidikan Anak Usia Dini, 2(2), 14. https:\/\/doi.org\/10.47134\/paud.v2i2.1272\r\nJEPIN (Jurnal Edukasi dan Penelitian Informatika) Pengolahan Korpus Dataset Audio Bacaan Al-Qur’an Menggunakan Metode Wav2Vec 2.0. (2024).\r\nKeterlambatan Bicara.pdf. (n.d.). IDAI, 2013.\r\nMaskur, M., & Zahra, A. (2025). The Impact of Data Augmentation Techniques on Improving Speech Recognition Performance for English in Indonesian Children Based on Wav2Vec 2.0. IJCCS (Indonesian Journal of Computing and Cybernetics Systems, 19(2), 165–176. https:\/\/doi.org\/10.22146\/ijccs.104646\r\nMochamad Suhri Ainur Rifky, Amalia Anjani Arifiyanti, & Reisa Permatasari. (2023). Analisis Sentimen Pengguna Youtube Mengenai Analog Switch Off Menggunakan Word Embedding Dan Metode Long Short-Term. Jurnal Teknik Mesin, Industri, Elektro Dan Informatika, 2(3), 195–202. https:\/\/doi.org\/10.55606\/jtmei.v2i3.2273\r\nMustari S. Lamada, Alimuddin Sa’ban Miru, & Riski Amalia. (2024). Pengujian Aplikasi Sistem Monitoring Perkuliahan Menggunakan Standar ISO 25010. Jurnal MediaTIK, 3(3), 1–7. https:\/\/doi.org\/10.59562\/mediatik.v3i3.1559\r\nNOERCHOLIS, A., DWIANDINI, T., & MUKTI, F. S. (2024). Optimasi Teknologi WAV2Vec 2.0 menggunakan Spectral Masking untuk meningkatkan Kualitas Transkripsi Teks Video bagi Tuna Rungu. ELKOMIKA: Jurnal Teknik Energi Elektrik, Teknik Telekomunikasi, & Teknik Elektronika, 12(4), 877. https:\/\/doi.org\/10.26760\/elkomika.v12i4.877\r\nPratama, R. S. A., & Amrullah, A. (2024). Analysis of Whisper Automatic Speech Recognition Performance on Low Resource Language. Jurnal Pilar Nusa Mandiri, 20(1), 1–8. https:\/\/doi.org\/10.33480\/pilar.v20i1.4633\r\nPutra, M. M. I., Sompie, S. R. U. A., & Paturusi, S. (2020). Implementation of Speech Recognition in English Learning Applications for Children. Jurnal Teknik Informatika, 15(4), 247–256. https:\/\/ejournal.unsrat.ac.id\/index.php\/informatika\/article\/view\/30426\r\nRahman, M. Z., Sari, Y. A., & Yudistira, N. (2021). Analisis Sentimen Tweet COVID-19 menggunakan Word Embedding dan Metode Long Short-Term Memory (LSTM). Jurnal Pengembangan Teknologi Informasi Dan Ilmu Komputer, 5(11), 5120–5127.\r\nRodiah, Susetianingtias, D. T., & Eka Patriya. (2024). Identifikasi Fitur Suara Menggunakan Model Convolutional Neural Network (CNN) pada Speech-to-Text (STT). Decode: Jurnal Pendidikan Teknologi Informasi, 4(3), 809–820. https:\/\/doi.org\/10.51454\/decode.v4i3.631\r\nTridarma, P., & Endah, S. N. (n.d.). Pengenalan Ucapan Bahasa Indonesia Menggunakan MFCC dan Recurrent Neural Network. In Jurnal Masyarakat Informatika (Vol. 11, Number 2)."
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