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All Journal International Journal of Electrical and Computer Engineering IAES International Journal of Artificial Intelligence (IJ-AI) ComEngApp : Computer Engineering and Applications Journal TELKOMNIKA (Telecommunication Computing Electronics and Control) Bulletin of Electrical Engineering and Informatics JSI: Jurnal Sistem Informasi (E-Journal) Jurnal Inovasi Hasil Pengabdian Masyarakat (JIPEMAS) Indonesian Journal of Electrical Engineering and Computer Science Sriwijaya Journal of Informatics and Applications Jurnal Mandiri IT
Muhammad Naufal Rachmatullah
Universitas Sriwijaya
Computer Science & IT Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Engineering Library & Information Science Mathematics Other

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Journal : Bulletin of Electrical Engineering and Informatics

 1 
Residual pixel-wise semantic segmentation for assessing enlarged fetal heart: a preliminary study Roseno, Muhammad Taufik; Nurmaini, Siti; Rini, Dian Palupi; Saputra, Tommy; Mirani, Putri; Rachmatullah, Muhammad Naufal; Darmawahyuni, Annisa; Sapitri, Ade Iriani; Syaputra, Hadi
Bulletin of Electrical Engineering and Informatics Vol 14, No 4: August 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i4.9244

Abstract

The four-chamber view is a crucial scan plane routinely employed in both second-trimester perinatal screening and fetal echocardiographic examinations. Sonographers typically measure biometrics in this plane, such as the cardiothoracic ratio (CTR) and heart axis, to diagnose fetal heart anomalies. However, due to the echocardiographic artifacts, the assessment not only suffers from low efficiency but also inconsistent results depending on the operators’ skills. This study proposes a residual pixel-wise semantic segmentation, which segmented the fetal heart and thoracic contours in a 4-chamber view for assessing an enlarged fetal heart condition. The accuracy of intersection-over-union (IoU) and dice coefficient similarity (DCS) is used for model validation to further regulate the evaluation procedure. We use 1174 US images, comprising about 560 enlarged heart images, and about 614 normal heart images. Out of these data, 248 images are used for unseen data, and the remaining for training/validation processes. The performance of the proposed model, when tested on unseen data, achieved satisfactory results with 97.71% accuracy, 90.36% IoU, and 94.93% DCS. These metrics collectively demonstrate the satisfactory performance of the proposed model compared to existing segmentation models. The outcomes underscore that the proposed model establishes a state-of-the-art standard for enlarged fetal heart detection.
Text clustering for analyzing scientific article using pre-trained language model and k-means algorithm Firdaus, Firdaus; Nurmaini, Siti; Yusliani, Novi; Rachmatullah, Muhammad Naufal; Darmawahyuni, Annisa; Kunang, Yesi Novaria; Fachrurrozi, Muhammad; Armansyah, Risky
Bulletin of Electrical Engineering and Informatics Vol 14, No 5: October 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v14i5.9670

Abstract

Text clustering is a technique in data mining that can be used for analyzing scientific articles. In Indonesia-accredited journals, SINTA, there are two languages used, Indonesian and English. This is the first research focusing on clustering Indonesian and English texts into one cluster. In this research, bidirectional encoder representations from transformers (BERT) and IndoBERT are used to represent text data into fixed feature vectors. BERT and IndoBERT are pre-trained language models (PLMs) that can produce vector representations that take care of the position and context in a sentence. To cluster the articles, the K-Means algorithm is implemented. This algorithm has good convergence and adapts to the new examples, which helps in improved clustering performance. The best k-value in the K-Means algorithm is defined by using the silhouette score, the elbow method, and the Davies-Bouldin index (DBI). The experiment shows that the silhouette score can produce the most optimal k-value in clustering the articles, which has a mean score of 0.597. The mean score for the elbow method is 0.425, and for the DBI is 0.412. Therefore, the silhouette score optimizes the performance of PLMs and the K-Means algorithm in analyzing scientific articles to determine whether in scope or out of scope.
Co-Authors Abdurahman Ade Iriani Sapitri Ade Iriani Sapitri Ahmad Rifai Ahmad Rizky Fauzan Akhiar Wista Arum Akhtiar W Arum Al Farissi Ananda, Dea Agustria Andre Herviant Juliano Anggun Islami Anggun Islami Anita Desiani Annisa Darmawahyuni Annisa Darmawahyuni Armansyah, Risky Arnaldo, Muhammad Arum, Akhiar Wista Bambang Tutuko Bambang Tutuko Bambang Tutuko Bayu Wijaya Putra Darmawahyuni, Annisa Darmawahyuni, Annisa Desty Rodiah Dewi Chayanti Dian Palupi Rini Dian Palupi Rini Dinda Lestarini Dite Geovanni Erwin, Erwin Fadel Muhammad, Fadel Fahreza, Irvan Firdaus Firdaus Firdaus Firdaus Firdaus Firdaus Firdaus Firdaus Firdaus Hadipurnawan Satria Hanif Habibie Supriansyah Irvan Fahreza Islami, Anggun Kurniawan, Anggy Tias M. Fachrurrozi . Maharani, Masayu Nadila Masayu Nadila Maharani Mira Afrina Muhammad Akmal Shidqi Muhammad Arnaldo Muhammad Fachrurrozi Muhammad Fachrurrozi Muhammad Gibran Al-Filambany Muhammad Irham Rizki Fauzi Muhammad Taufik Roseno, Muhammad Taufik Novi Yusliani Patiyus Agustiansyah PATIYUS AGUSTIANSYAH, PATIYUS Putri Mirani Rahmat Fadli Isnanto Raihan Mufid Setiadi Raihan Mufid Setiadi Renny Amalia Pratiwi Reza Firsandaya Malik Ricy Firnando Ricy Firnando Rossi Passarella Samsuryadi Samsuryadi Sapitri, Ade Iriani Saputra, Tommy Sari, Ririn Purnama Sarifah Putri Raflesia, Sarifah Putri Sastradinata, Irawan Setiadi, Raihan Mufid Siti Nurmaini Sri Indra Maiyanti Suci Dwi Lestari Suci Dwi Lestari Sugandi Yahdin Sukemi Sukemi Sukemi Sutarno Sutarno Sutarno Syaputra, Hadi Tio Artha Nugraha Varindo Ockta Keneddi Putra Yesi Novaria Kunang