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All Journal Journal of Information Technology and Its Utilization
Atikah Dhani Ayuningtyas
Syarif Hidayatullah State Islamic University Jakarta
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Mechanical Engineering

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NEXT WORD PREDICTION USING LSTM Afika Rianti; Suprih Widodo; Atikah Dhani Ayuningtyas; Fadlan Bima Hermawan
Journal of Information Technology and Its Utilization Vol 5, No 1 (2022)
Publisher : Sekolah Tinggi Multi Media (STMM) Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.30818/jitu.5.1.4748

Abstract

Next word prediction which is also called as language modelling is one field of natural language processing that can help to predict the next word. It’s one of the uses of machine learning. Some researchers before had discussed it using different models such as Recurrent Neural Networks and Federated Text Models. Each researcher used their own models to make the prediction and so the researcher here. Researchers here chose to make the model using  Long Short Term Memory (LSTM) model with 200 epoch for the training. For the dataset, the researcher used web scraping. The dataset contains 180 Indonesian destinations from nine provinces. For the libraries, researchers used  tensorflow, keras, numpy, and matplotlib. To download the model in json format, the researcher used tensorflowjs. Then for the tool to code, the researcher used Google Colab. The last result is 8ms/step, loss: 55%, and accuracy: 75% which means it’s good enough and can be used to predict next words.
NEXT WORD PREDICTION USING LSTM Afika Rianti; Suprih Widodo; Atikah Dhani Ayuningtyas; Fadlan Bima Hermawan
Journal of Information Technology and Its Utilization Vol 5 No 1 (2022)
Publisher : Sekolah Tinggi Multi Media "MMTC" Yogyakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56873/jitu.5.1.4748

Abstract

Next word prediction which is also called as language modelling is one field of natural language processing that can help to predict the next word. It’s one of the uses of machine learning. Some researchers before had discussed it using different models such as Recurrent Neural Networks and Federated Text Models. Each researcher used their own models to make the prediction and so the researcher here. Researchers here chose to make the model using  Long Short Term Memory (LSTM) model with 200 epoch for the training. For the dataset, the researcher used web scraping. The dataset contains 180 Indonesian destinations from nine provinces. For the libraries, researchers used  tensorflow, keras, numpy, and matplotlib. To download the model in json format, the researcher used tensorflowjs. Then for the tool to code, the researcher used Google Colab. The last result is 8ms/step, loss: 55%, and accuracy: 75% which means it’s good enough and can be used to predict next words.
Co-Authors Afika Rianti Fadlan Bima Hermawan Suprih Widodo, Suprih