• Afika Rianti Indonesia University of Education
  • Suprih Widodo Indonesia University of Education
  • Atikah Dhani Ayuningtyas Syarif Hidayatullah State Islamic University Jakarta
  • Fadlan Bima Hermawan Syarif Hidayatullah State Islamic University Jakarta



Machine learning, Next word prediction, LSTM


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.


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How to Cite

Rianti, A., Widodo, S., Ayuningtyas, A. D., & Hermawan, F. B. (2022). NEXT WORD PREDICTION USING LSTM. Journal of Information Technology and Its Utilization, 5(1), 10–13.