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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) eProceedings of Engineering Jurnal INFOTEL Cahaya Pengabdian
Aditya Firman Ihsan
Telkom University
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 : Building of Informatics, Technology and Science

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The Organization Entity Extraction Telkom University Affiliated using Recurrent Neural Network (RNN) Muhammad Daffa Regenta Sutrisno; Donni Richasdy; Aditya Firman Ihsan
Building of Informatics, Technology and Science (BITS) Vol 4 No 2 (2022): September 2022
Publisher : Forum Kerjasama Pendidikan Tinggi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47065/bits.v4i2.1956

Abstract

In the news portal text, there is a lot of important information such as the name of the person, the name of the organization, or the name of the place. To obtain information in text documents manually, humans must read the contents of the entire news text. To overcome this issue, information extraction, commonly called Named Entity Recognition (NER) was used. The extraction of information expressly for the NER field is used to make it easier to process word or sentence data. It helps search engines and also helps to classify places, times, and organizations. There is a limited number of NER in Indonesian texts using only the Recurrent Neural Network (RNN) method. Similar previous studies only employed other versions of RNN such as LSTM (Long Short Term Memory), BiLSTM (Bidirectional Long Short Term Memory), and CNN (Convolutional Neural Network). NER is one of the answers to the problems that exist in a large number of news portal texts to obtain information effectively and efficiently. The results of this study indicate that the NER system using the RNN method in Indonesian news texts has an F1 -Score of 80%
Co-Authors Alif Adwitiya Pratama Andi Fadil Adiyaksa Conny Tria Shafira Djatnika Widia Nugraha Donni Richasdy Donny Richasdy Hery Widijanto Indidharmanto, Ahmad Maulana Made Mita Wikantari Mahmud Dwi Sulistiyo Muhammad Daffa Regenta Sutrisno Muhammad Helmy Faishal Muzakky, Faqih Ahmad Puteri, Nurhidayah Putra, Rachmat Dwi Putu Harry Gunawan Raisa Benaya Rheza Ramadhan Putra Shuhaimi Mahadzir Sri Suryani Prasetiyowati Sujadi, Cika Carissa Sulistyo, Mahmud Dwi Uruqul Nadhif Dzakiy Widi Astuti Yuliant Sibaroni Yusuf, Afrizal Syahruluddin