Jurnal
SINTA 1
Pre-trained BERT Architecture Analysis for Indonesian Question Answer Model
Journal of Applied Engineering and Technological Science (JAETS)
ISSN 2715-6079, 2715-6087
Terbit 2024-12-15
Penerbit Yayasan Riset dan Pengembangan Intelektual (YRPI)
Bahasa en
Abstrak
Developing a question-and-answer system in Natural Language Processing (NLP) has become a major concern in the Indonesian language context. One of the main challenges in developing a question-and-answer system is the limited dataset, which can cause instability in system performance. The limitations of the dataset make it difficult for the question-and-answer model to understand and answer questions well. The proposed solution uses Transfer Learning with pre-trained models such as BERT. This research aims to analyze the performance of the BERT model, which has been adapted for question-and-answer tasks in Indonesian. The BERT model uses an Indonesian language dataset adapted specifically for question-and-answer tasks. A customization approach tunes BERT parameters according to the given training data. The results obtained; the model is improved by minimizing the loss function. Evaluation of the trained model shows that the best validation loss is 0.00057 after 150 epochs. In addition, through in-depth evaluation of the similarity of question texts, the BERT model can answer questions measurably, according to existing knowledge in the dataset.
Jaringan kolaborasi para penulis
14 penulis ·
51 tautan kepenulisan bersama
· 9 lintas organisasi
Arahkan kursor atau ketuk sebuah nama untuk menyorot rekan penulisnya. Klik dua kali untuk membuka halaman penulis.
Garis lebih tebal = lebih banyak artikel bersama · lingkaran lebih besar = lebih banyak artikel
Tampilkan sebagai tabel
Afiliasi berasal dari OpenAlex; metadata OAI-PMH jurnal tidak memuatnya. Penulis tanpa ID OpenAlex dicocokkan berdasarkan nama, sehingga dua orang bisa tergabung atau satu orang bisa terpisah.
Sumber metadata: OAI-PMH (metadata jurnal) https://journal.yrpipku.com/index.php/jaets/oai, pertama di-harvest 9 Nov 2026, terakhir terlihat 9 Nov 2026.
Metadata asli (oai_dc)
<oai_dc:dc xmlns="http://www.openarchives.org/OAI/2.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd">
<dc:title xml:lang="en">Pre-trained BERT Architecture Analysis for Indonesian Question Answer Model</dc:title>
<dc:creator xml:lang="en">Sudianto, Sudianto</dc:creator>
<dc:subject xml:lang="en">BERT</dc:subject>
<dc:subject xml:lang="en">Chatbot</dc:subject>
<dc:subject xml:lang="en">Indonesian</dc:subject>
<dc:subject xml:lang="en">NLP</dc:subject>
<dc:subject xml:lang="en">Transfer Learning</dc:subject>
<dc:subject xml:lang="en">Question Answer</dc:subject>
<dc:description xml:lang="en">Developing a question-and-answer system in Natural Language Processing (NLP) has become a major concern in the Indonesian language context. One of the main challenges in developing a question-and-answer system is the limited dataset, which can cause instability in system performance. The limitations of the dataset make it difficult for the question-and-answer model to understand and answer questions well. The proposed solution uses Transfer Learning with pre-trained models such as BERT. This research aims to analyze the performance of the BERT model, which has been adapted for question-and-answer tasks in Indonesian. The BERT model uses an Indonesian language dataset adapted specifically for question-and-answer tasks. A customization approach tunes BERT parameters according to the given training data. The results obtained; the model is improved by minimizing the loss function. Evaluation of the trained model shows that the best validation loss is 0.00057 after 150 epochs. In addition, through in-depth evaluation of the similarity of question texts, the BERT model can answer questions measurably, according to existing knowledge in the dataset.&nbsp; </dc:description>
<dc:publisher xml:lang="en">Yayasan Riset dan Pengembangan Intelektual (YRPI)</dc:publisher>
<dc:date>2024-12-15</dc:date>
<dc:type>info:eu-repo/semantics/article</dc:type>
<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
<dc:format>application/pdf</dc:format>
<dc:identifier>https://journal.yrpipku.com/index.php/jaets/article/view/4746</dc:identifier>
<dc:identifier>10.37385/jaets.v6i1.4746</dc:identifier>
<dc:source xml:lang="en">Journal of Applied Engineering and Technological Science (JAETS); Vol. 6 No. 1 (2024): Journal of Applied Engineering and Technological Science (JAETS); 60-68</dc:source>
<dc:source>2715-6079</dc:source>
<dc:source>2715-6087</dc:source>
<dc:source>10.37385/jaets.v6i1</dc:source>
<dc:language>en</dc:language>
<dc:relation>https://journal.yrpipku.com/index.php/jaets/article/view/4746/3632</dc:relation>
<dc:rights xml:lang="en">Copyright (c) 2024 Journal of Applied Engineering and Technological Science (JAETS)</dc:rights>
</oai_dc:dc>
Sitasi dan pengindeksan
OpenAlex
Terindeks
lewat DOI
6 sitasi
Crossref
Belum diperiksa
Jumlah menurut tiap indeks pada 13 Nov 2026; setiap indeks menghitung sitasi dengan cara berbeda.
OpenAlex juga mencatat karya ini di: crossref, doaj.
Sitasi artikel ini
APA 7
Sudianto, S. (2024). Pre-trained BERT Architecture Analysis for Indonesian Question Answer Model. Journal of Applied Engineering and Technological Science (JAETS), 6(1), 60–68. https://doi.org/10.37385/jaets.v6i1.4746
Salin
IEEE
S. Sudianto, “Pre-trained BERT Architecture Analysis for Indonesian Question Answer Model,” Journal of Applied Engineering and Technological Science (JAETS), vol. 6, no. 1, pp. 60–68, 2024, doi: 10.37385/jaets.v6i1.4746.
Salin
Dibuat dari metadata jurnal; periksa nama penulis sebelum dipakai.