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VOICE RECOGNITION, TEXT CORRECTION FROM INDONESIAN SPEAKING BASED ON NLP AND TEXT MINING
Erwina, Emmy () 2023Today information technologies play an increasingly significant role in society. The technology development has already reached such a level that large corporations are beginning to use systems not only for processing information, but also for forecasting certain processes in society, nature, economy and other spheres of human life. One of these ways of processing information without using human resources is neural networks. The scientific novelty is determined by the fact that the article explores the symbolic analysis of text using a neural network. Recognition of written characters using a neural network could be useful for psychological studies of the relationship between a person's psychological state and his handwriting. As can be found out in a person's handwriting, the size of a slope, the direction of the letters, the pressure on a pen and the nature of lettering itself are important. If to combine a neural network for recognising written signs and a database of handwriting of many people, interesting statistics can be seen and the attempt to find connection between handwriting and character can be made. The practical significance of the research is determined by the fact that the research results can be used by specialists in different fields. The main problem in these cases is an optimised written character recognition algorithm that can correctly and quickly recognise written characters. Based on this, the object of research is the algorithm for recognising written characters, and the subject of research is the neural network itself.
WORD FORMATION USED IN NEWS APPLICATION “SOOMPI”
Nazogi, Rizky Meilida () 2019Penelitian ini bertujuan untuk menganalisis Formasi Kata dalam artikel-artikel Aplikasi Berita. Penelitian ini mendeskripsikan proses pembentukan kata yang didukung dengan teori dari George Yule (2010) yaitu untuk mengetahui bagaimana proses pembentukan kata yang digunakan dalam artikel News Application “Soompi”. Data dalam penelitian ini diambil dari Aplikasi Berita “Soompi”, buku teks, jurnal, dan sumber lainnya. Penelitian ini menggunakan metode deskriptif kualitatif yang mengandalkan data verbal dan dijelaskan secara deskriptif. Penulis menemukan bahwa ada 30 kemunculan Formasi kata yang digunakan dalam artikel pada Aplikasi Berita yaitu Compounding dengan 10 kemunculan (33,33 %), Derivation dengan 7 kemunculan (23,33 %), Akronim dengan 7 kemunculan (23,33 %), %), Blending dengan 2 kejadian (6,66 %), Meminjam dengan 2 kejadian (6,66 %), dan Clipping dengan 2 kejadian (6,66 %). Berdasarkan hasil penelitian, penulis menemukan jenis pembentukan kata yang paling dominan digunakan pada Aplikasi Berita “Soompi” adalah Derivasi.