Implementasi Speech to Text untuk Mempermudah Catatan Praktik Diagnosis Pasien Dengan Metode NLP
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Abstract
Medical diagnoses in students' field study practice activities are very important, as data in preparing field study practice reports. The large amount of diagnostic data that has to be retyped manually makes time ineffective. Based on this problem, this research implements Speech to Text (STT), a feature that can convert voice into text using the Natural Language Processing (NLP) method using the Python programming language. The NLP method is used in this research because its role is to interpret a language, both written and spoken, so it really supports the operation of STT. Students just need to record the diagnostic conversation with the patient, then the .wav format file is processed in a system that will provide written output, so students just have to copy it into a report. The test used some audio files that had different durations and noise levels. The system can convert voice into text with a success percentage of 93,34%.
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References
A, V., & V. Jose, D. (2019). Speech To Text Conversion And Summarization For Effective Understanding And Documentation. International Journal Of Electrical Computer Engineering (Ijece), 9(5), 3642–3648.
Adnan, F., Amelia, I., & Shiddiq, S. ’Umar. (2022). Implementasi Voice Recognition Berbasis Machine Learning. Edu Elektrika, 11(1), 24–29.
Darwin, D., Anwar, M., & Munir, M. (2021). Paradigma Strukturalisme Bahasa: Fonologi, Morfologi, Sintaksis, Dan Semantik. Jurnal Ilmiah Semantika, 2(2), 28–40.
Http://Jurnal.Umus.Ac.Id/Index.Php/Semanti Ka
Dwijayanti, S., Tami, M. A., & Suprapto, B. Y. (2021). Speech-To-Text Conversion In Indonesian Language Using A Deep Bidirectional Long Short-Term Memory Algorithm. (Ijacsa) International Journal Of Advanced Computer Science And Applications, 12(3), 225–230.
Fuad, R. N., & Winata, H. N. (2019). Aplikasi Keamanan File Audio Wav (Waveform) Dengan Terapan Algoritma Rsa. Jurnal Nasional Informatika Dan Teknologi Jaringan, 1(2), 113–119.
Gani, S., & Arsyad, B. (2019). Kajian Teoritis Struktur Internal Bahasa (Fonologi, Morfologi, Sintaksis, Dan Semantik) . A Jamiy, Jurnal Bahasa Dan Sastra Arab, 7(1), 1–20.
Guntara, R. G., Nuryadin, A., & Hartanto, B. (2021). Pemanfaatan Google Speech To Text Untuk Aplikasi Pembelajaran Kamus Bahasa Sunda Pada Platform Mobile Android . Justek : Jurnal Sains Dan Teknologi, 4(1), 10–19.
Hermawan, N. F., Kuswoyo, & Nafi’i, W. (2021). Fonetik: Artikulatoris, Akustis Dan Auditoris Serta Pengajarannya. El Wahdah, 2(1), 1–13.
Irdamurni, & Taufan, J. (2019). Implementation Of Speech To-Text Application For Deaf Students On Inclusive Education Course. Journal Of Icsar, 3(2), 38–40.
M Fahrurrozi, & Kurniawan, A. (2021). Diagnosis Dalam Proses Keperawatan: Literature Review. Jurnal Ilmiah Kesehatan Fakultas Ilmu Kesehatan Universitas Sains Al-Qur’an Jawa Tengah, 11, 75–80.
Murnisma, Darwis, Mm., & Abbas, A. (2022). Pengaruh Unsur Sintaksis Bahasa Inggris Terhadap Penggunaan Bahasa Indonesia Imigran Afganistan. Jurnal Ilmu Budaya, 10(1).
Nugroho, K. (2019). Implementasi Sistem Speech To Text Berbasis Android Menggunakan App Inventor Speech Recognition. Jurnal Ilmiah Informasi Komputer Akuntansi Dan Manajemen (Infokam), Amik Jtc Semarang, 15, 38–43.
Nurfiyah, & Ramadhandi, N. (2024). Penerapan Metode Natural Language Processing (Nlp) Pada Question Answering System Untuk Media Informasi Mahasiswa Universitas Bhayangkara Jakarta Raya. Journalofinformationandinformationsecur Ity(Jiforty), 4, 175–186.
Ramadahnti, F., Wibisono, Y., & Sukamto, R. A. (2019). Analisis Morfologi Untuk Menangani Out Ofvocabulary Words Pada Part-Of-Speech Tagger Bahasa Indonesia Menggunakan Hidden Markov Model. Jurnal Linguistik Komputasional, 2(1), 6–12.
Setiawan, E. (2024, June 4). Kbbi. Https://Www.Kbbi.Web.Id/Diagnosis.
Soyusiawaty, D. (2023). Buku Ajar Pemrosesan Bahasa Alami. Laboratorium Teknik Informatika Universitas Ahmad Dahlan. Https://Eprints.Uad.Ac.Id/47839/1/Diktat%2 0pba%20genap%202023.Pdf (1) Persamaan Perhitungan Persentase Tingkat Akurasi Deteksi Oleh Sistem.