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All Journal Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL MEDIA INFORMATIKA BUDIDARMA Indonesian Journal of Artificial Intelligence and Data Mining Communication in Biomathematical Sciences JIPI (Jurnal Ilmiah Penelitian dan Pembelajaran Informatika) Building of Informatics, Technology and Science JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Journal of Computer System and Informatics (JoSYC) Charity : Jurnal Pengabdian Masyarakat eProceedings of Engineering Jurnal INFOTEL Cahaya Pengabdian
Aditya Firman Ihsan
Telkom University
Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Engineering Industrial & Manufacturing Engineering Social Sciences Other

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Journal : Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi)

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On the Neural Network Solution of One-Dimensional Wave Problem Aditya Firman Ihsan
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 5 No 6 (2021): Desember 2021
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (493.957 KB) | DOI: 10.29207/resti.v5i6.3565

Abstract

Artificial neural network has become an emerging popular method to handle various problems, especially in case where it has deep multiple neural layers. In this study, we use a deep artificial neural network model to solve one-dimensional wave equation, without any external datasets. Different type of boundary conditions, i.e., Dirichlet, Neumann, and Robin, are used. We analyze the model learning capabilities in a set of settings, such as data setup and the model width and depth. We also present some discussions of advantages and disadvantages of the model in comparison with other matured existing techniques to solve wave equation.
Pengenalan Tulisan Tangan Aksara Bali Menggunakan Faster R-CNN Pratama, Alif Adwitiya; Sulistiyo, Mahmud Dwi; Ihsan, Aditya Firman
Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Vol 7 No 6 (2023): December 2023
Publisher : Ikatan Ahli Informatika Indonesia (IAII)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.29207/resti.v7i6.5176

Abstract

In Balinese culture, the ability to read Balinese script is one of the challenges young generations face. Advances in machine learning have proposed handwriting detection systems using both traditional and deep learning models. However, the traditional approach is usually impractical and is prone to inaccurate identification results. Convolutional neural network (CNN)-based models integrate feature extraction and classification into an end-to-end pipeline to increase performance. This research proposes that recognizing characters through an object detection approach makes an end-to-end process of localizing and classifying several characters simultaneously using the Faster R-CNN. Four CNN models, including ResNet-50, ResNet-101, ResNet-152, and Inception ResNet V2, were tested to detect 28 Balinese characters in a single form that covers 18 consonants and 10 digits using Intersection over Union (IoU) thresholds: 0.5 and 0.75. ResNet-50 and Inception ResNet V2 achieve 0.991 mAP at IoU of 0.5, while Inception ResNet V2 excels at IoU of 0.75. Further analysis showed that the class ‘nol’ had the lowest Recall due to many undetected ground truths. Meanwhile, class ‘ba’ had the lowest Precision due to its similarity to classes “ga” and “nga”. This research contributes to the experiment with Faster R-CNN in detecting handwritten Balinese scripts.
Co-Authors Andi Fadil Adiyaksa Conny Tria Shafira Deni Saepudin Didit Adytia Djatnika Widia Nugraha Donni Richasdy Donny Richasdy Hery Widijanto Indidharmanto, Ahmad Maulana Made Mita Wikantari Mahadzir, Shuhaimi Mahmud Dwi Sulistiyo Muhammad Daffa Regenta Sutrisno Muhammad Helmy Faishal Muzakky, Faqih Ahmad Pratama, Alif Adwitiya Puteri, Nurhidayah Putra, Rachmat Dwi Putu Harry Gunawan Raisa Benaya Rheza Ramadhan Putra Sri Suryani Prasetiyowati Sujadi, Cika Carissa Sulistyo, Mahmud Dwi Uruqul Nadhif Dzakiy Widi Astuti Yuliant Sibaroni Yusuf, Afrizal Syahruluddin