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All Journal International Journal of Electrical and Computer Engineering Tekno : Jurnal Teknologi Elektro dan Kejuruan Transmisi: Jurnal Ilmiah Teknik Elektro Mechatronics, Electrical Power, and Vehicular Technology Bulletin of Electrical Engineering and Informatics Jurnal Ilmiah Teknik Elektro Komputer dan Informatika (JITEKI) Jurnal Informatika dan Teknik Elektro Terapan Proceeding of the Electrical Engineering Computer Science and Informatics CIRCUIT: Jurnal Ilmiah Pendidikan Teknik Elektro SELAPARANG: Jurnal Pengabdian Masyarakat Berkemajuan CCIT (Creative Communication and Innovative Technology) Journal Abdimas: Jurnal Pengabdian Masyarakat Universitas Merdeka Malang Jurnal E-Komtek Frontier Energy System and Power Engineering Community Development Journal: Jurnal Pengabdian Masyarakat JTEIN: Jurnal Teknik Elektro Indonesia Bulletin of Community Engagement Jurnal Teknik Elektro Jurnal Teknik Informatika dan Elektro (JURTIE) Prosiding Seminar Nasional Pengabdian Kepada Masyarakat ABDI UNISAP: Jurnal Pengabdian Kepada Masyarakat Power Elektronik : Jurnal Orang Elektro Jurnal Ecotipe (Electronic, Control, Telecommunication, Information, and Power Engineering) KOPEMAS
Langlang Gumilar
Universitas Negeri Malang
Religion Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Nursing Public Health Social Sciences Other

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Journal : International Journal of Electrical and Computer Engineering

 1 
Detecting emotions using a combination of bidirectional encoder representations from transformers embedding and bidirectional long short-term memory Wibawa, Aji Prasetya; Cahyani, Denis Eka; Prasetya, Didik Dwi; Gumilar, Langlang; Nafalski, Andrew
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 6: December 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i6.pp7137-7146

Abstract

One of the most difficult topics in natural language understanding (NLU) is emotion detection in text because human emotions are difficult to understand without knowing facial expressions. Because the structure of Indonesian differs from other languages, this study focuses on emotion detection in Indonesian text. The nine experimental scenarios of this study incorporate word embedding (bidirectional encoder representations from transformers (BERT), Word2Vec, and GloVe) and emotion detection models (bidirectional long short-term memory (BiLSTM), LSTM, and convolutional neural network (CNN)). With values of 88.28%, 88.42%, and 89.20% for Commuter Line, Transjakarta, and Commuter Line+Transjakarta, respectively, BERT-BiLSTM generates the highest accuracy on the data. In general, BiLSTM produces the highest accuracy, followed by LSTM, and finally CNN. When it came to word embedding, BERT embedding outperformed Word2Vec and GloVe. In addition, the BERT-BiLSTM model generates the highest precision, recall, and F1-measure values in each data scenario when compared to other models. According to the results of this study, BERT-BiLSTM can enhance the performance of the classification model when compared to previous studies that only used BERT or BiLSTM for emotion detection in Indonesian texts.
Hybrid deep learning for estimation of state-of-health in lithium-ion batteries Cahyani, Denis Eka; Gumilar, Langlang; Afandi, Arif Nur; Wibawa, Aji Prasetya; Junoh, Ahmad Kadri
International Journal of Electrical and Computer Engineering (IJECE) Vol 15, No 1: February 2025
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v15i1.pp995-1006

Abstract

Lithium-ion (li-ion) batteries have a high energy density and a long cycle life. Lithium-ion batteries have a finite lifespan, and their energy storage capacity diminishes with use. In order to properly plan battery maintenance, the state of health (SoH) of lithium-ion batteries is crucial. This study aims to combine two deep learning techniques (hybrid deep learning), namely convolutional neural network (CNN) and bidirectional long short-term memory (BiLSTM), for SoH estimation in li-ion batteries. This study contrasts hybrid deep learning methods to single deep learning models so that the most suitable model for accurately measuring the SoH in lithium-ion batteries can be determined. In comparison to other methodologies, CNN-BiLSTM yields the best results. The CNN-BiLSTM algorithm yields RMSE, mean square error (MSE), mean absolute error (MAE), and mean absolute percentage error (MAPE) in the following order: 0.00916, 0.000084, 0.0048, and 0.00603. This indicates that CNN-BiLSTM, as a hybrid deep learning model, is able to calculate the approximate capacity of the lithium-ion battery more accurately than other methods.
Co-Authors A.N. Afandi Abdullah Iskandar Syah Abdullah Iskandar Syah Achmad Fahrul Aji Achmad Fakhri Achmad Safi’i Achmad Syahrudin Fakhri Afandi, Arif Agil Ziddan Achmad Ahmad Dhaffa' Nibrosoma Aji Prasetya Wibawa Andriansyah, Muhammad Rizal Anik Nur Handayani Anjar Dwi Hariadi Arie Muazib Arif Afandi Aripriharta - Arum Kusuma Wardhany Asfani, Khoirudin Ayu Puwatiningsih Denis Eka Cahyani Dhiyaurrahman Fakhruddin Didik Dwi Prasetya Dita Anies Munawwaroh Dito Valentino Dityo Kreshna Argeshwara Diva Ayu Lestari Dwi Mukti Asmoro Eka Mistakim Erry Asnarindra Faisal Farris Setyawan Fakhri, Achmad Syahrudin Fakhruddin, Dhiyaurrahman Falah, Moh. Zainul Farah Wardatul Afifah Farrel Candra WA Fitri Zakiyatul Azizah Gilang Indrianto Pramono Gunawan, M. Ricko Hariadi, Anjar Dwi Ihsan, Rifqi Al Inov Ivandany Ira Kumalasari Irham Fadlika Joumil Aidil Saifuddin Junoh, Ahmad Kadri Kornelius Kamargo/Irawan Dwi Wahyono Kornelius Kamargo Kusumawardana, Arya M Rodhi Faiz M. Cahyo Bagaskoro M. Farrel Akbar Firzatullah Michiko Ryuu Sakura A Mistakim, Eka Moh Zainul Falah Moh. Zainul Falah Moh. Zainul Falah Mohamad Rodhi Faiz Monika, Dezetty Muchamad Wahyu Prasetyo Muhammad Afnan Habibi Muhammad Andriansyah Muhammad Arzu Prasetyo Muhammad As’ad Sahroni Muhammad Ihsanul Rizqi Muhammad Jazuli Shubhi Muhammad Jazuli Shubhi Muhammad Rizal Andriansyah Muhammad Sadidul Itqon Mutiar, Mutiar Muttabik Fathul Lathief Nafalski, Andrew Naizatul Zainul Rofiqi Nikmah, Revalina Nazilatun Nugraha, Agil Zaidan Nur Hidayat, Wahyu Quota Sias Rafli Amirul Husain Ridho Riski Hadi Ridzki, Imron Riya Mustikasari Rodhi Faiz Rumokoy, Steven N. Sakura A, Michiko Ryuu Samat, Ahmad Asri Abd Samsul Setumin Setumin, Samsul Setyawan, Faisal Farris Sias, Quota Alief Siti Sendari Soraya Norma Mustika Sujito - Sujito Sujito Sujito Sujito Syah, Abdullah Iskandar Syamsul Arifin Tran Huy Duy Utomo, Imam Tree WA, Farrel Candra Wahyu Tri Handoko Wahyu Tri Handoko Wicaksono, Ibram Adib Yogi Dwi Mahandi Yuni Rahmawati Yunis Sulistyorini Yunis Sulistyorini, Yunis