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All Journal International Journal of Electrical and Computer Engineering Bulletin of Electrical Engineering and Informatics ComTech: Computer, Mathematics and Engineering Applications Engineering, Mathematics and Computer Science Journal (EMACS)
Derwin Suhartono
Bina Nusantara University
Civil Engineering, Building, Construction & Architecture Computer Science & IT Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Mathematics

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Journal : Bulletin of Electrical Engineering and Informatics

 1 
Hoax analyzer for Indonesian news using RNNs with fasttext and glove embeddings Ryan Adipradana; Bagas Pradipabista Nayoga; Ryan Suryadi; Derwin Suhartono
Bulletin of Electrical Engineering and Informatics Vol 10, No 4: August 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v10i4.2956

Abstract

Misinformation has become an innocuous yet potentially harmful problem ever since the development of internet. Numbers of efforts are done to prevent the consumption of misinformation, including the use of artificial intelligence (AI), mainly natural language processing (NLP). Unfortunately, most of natural language processing use English as its linguistic approach since English is a high resource language. On the contrary, Indonesia language is considered a low resource language thus the amount of effort to diminish consumption of misinformation is low compared to English-based natural language processing. This experiment is intended to compare fastText and GloVe embeddings for four deep neural networks (DNN) models: long short-term memory (LSTM), bidirectional long short-term memory (BI-LSTM), gated recurrent unit (GRU) and bidirectional gated recurrent unit (BI-GRU) in terms of metrics score when classifying news between three classes: fake, valid, and satire. The latter results show that fastText embedding is better than GloVe embedding in supervised text classification, along with BI-GRU + fastText yielding the best result.
Indonesian automatic short answer grading system Heinrich Reagan Salim; Chintya De; Nicholas Daniel Pratamaputra; Derwin Suhartono
Bulletin of Electrical Engineering and Informatics Vol 11, No 3: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v11i3.3531

Abstract

Short answer question is one of the methods used to evaluate student cognitive abilities, including memorizing, designing, and freely expressing answers based on their thoughts. Unfortunately, grading short answers is more complicated than grading multiple choices answers. For that problem, several studies have tried to build an artificial intelligence system called automatic short answer grading (ASAG). We tried to improve the accuracy of the ASAG system at scoring student answers in Indonesian by enhancing the earlier state-of-the-art models and methods. They were the bidirectional encoder representations from transformer (BERT) with fine-tuning approach and ridge regression models utilizing advanced feature extraction. We conducted this study by doing stages of literature review, data set preparation, model development, implementation, and comparison. Using two different ASAG data sets, the best result of this study was an achievement of 0.9508 in pearson’s correlation and 0.4138 in root-mean-square error (RMSE) by the BERT-based model with the fine-tuning approach. This result outperformed the results of the previous studies using the same evaluation metrics. Thus, it proved our ASAG system using the BERT model with fine-tuning approach can improve the accuracy of grading short answers.
Co-Authors Andhika Rizki Pratama Antoni Wiguna Bagas Pradipabista Nayoga Billy Wibowo Chintya De Christian Eka Saputra Daniel D. Albesta Farhan Putra Salsabil Ferlan Gisman Putra Gabriel Nathaniel Gerardo Axel Lwiantoro Gregorius A. N. Aditantyo Hans Christian Heinrich Reagan Salim Helen Clarissa Irfan Fahmi Saputra Ivan Christanno Jody Johansyah Maulana Michael L. Jonathan Mikhael Pramodana Agus Muhammad Jawad Ngarap Imanuel Manik Nicholas Daniel Pratamaputra Oktovianus Hardiawan Priscilla Priscilla Rini Wongso Ryan Adipradana Ryan Suryadi Veronica Ong William Surya Permana Yunggih Nursalim