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All Journal International Journal of Electrical and Computer Engineering JURNAL SISTEM INFORMASI BISNIS TELKOMNIKA (Telecommunication Computing Electronics and Control) Prosiding Seminar Nasional Sains Dan Teknologi Fakultas Teknik Speed - Sentra Penelitian Engineering dan Edukasi Telematika Jurnal Transformatika Jurnal Informatika Upgris E-Dimas: Jurnal Pengabdian kepada Masyarakat JOIN (Jurnal Online Informatika) Prosiding 2nd Seminar Nasional IPTEK Terapan (SENIT) 2017 Sinkron : Jurnal dan Penelitian Teknik Informatika Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) Bianglala Informatika : Jurnal Komputer dan Informatika Akademi Bina Sarana Informatika Yogyakarta Indonesian Journal on Software Engineering (IJSE) JURNAL PENGABDIAN KEPADA MASYARAKAT Sarwahita : Jurnal Pengabdian Kepada Masyarakat EVOLUSI : Jurnal Sains dan Manajemen Jurnal Program Kemitraan dan Pengabdian Kepada Masyarakat Indonesian Journal of Networking and Security - IJNS Abdiformatika: Jurnal Pengabdian Masyarakat Informatika Jurnal Pengabdian Mitra Masyarakat (JPMM) Jurnal Sistem Informasi Jurnal DIMASTIK
Victor Gayuh Utomo
Program Studi Sistem Informasi, Fakultas Teknologi Informasi Dan Komunikasi, Universitas Semarang
Agriculture, Biological Sciences & Forestry Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Law, Crime, Criminology & Criminal Justice Library & Information Science Medicine & Pharmacology Social Sciences Other

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Benchmarking IndoBERT and Transformer Models for Sentiment Classification on Indonesian E-Government Service Reviews Dhendra; Victor Gayuh Utomo
Jurnal Transformatika Vol. 23 No. 1 (2025): July 2025
Publisher : Jurusan Teknologi Informasi Universitas Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26623/transformatika.v23i1.12095

Abstract

The rapid adoption of e-government services in Indonesia has increased the importance of understanding public sentiment toward digital platforms. This study presents a comparative analysis of five models—IndoBERT, mBERT, XLM-R, CNN, and BiLSTM—for sentiment classification on user reviews of NEWSAKPOLE, a public service application for vehicle tax and licensing. A custom dataset of 11,000+ reviews was scraped from the Google Play Store and labeled using a hybrid rating-based and manual validation approach. Each model was evaluated using accuracy, precision, recall, and F1-score. IndoBERT achieved the highest performance with an F1-score of 0.882, outperforming multilingual and classical deep learning models. Confusion matrix analysis showed that transformer-based models were more effective in detecting neutral and mixed sentiments, while CNN and BiLSTM struggled with misclassification. The results highlight IndoBERT's robustness in low-resource sentiment analysis and its potential to enhance public service monitoring and policy feedback mechanisms in Indonesian digital governance.
Co-Authors ., Pranoto Agusta Praba Ristadi Pinem Ahmad Rifa'i Apriyanto, Riski Ardima, Muhammad Basyier Arief Hidayat Arief Hidayat Arief Hidayat Aris Sugiharto Asmiatun, Siti Astrid Novita Putri, Astrid B. Rini Heryanti Bernadus Very Christoko Charis Maulana Cholil, Saifur Rohman Dhendra Eka Putri Rachmawati Febrian Wahyu Christanto Fitro Nur Hakim Galih Setiarso Handayani, Sri Hardani Widhiastuti Hassanudin, Wahyu Maulana Henny Indriyawati Henry Anggoro Djohan Hetty Catur Ellyawati, Hetty Catur Imam Wicaksono Kumkamdhani, Tirta Yurista Kusumaningrum, Yulinda Markus Nanang I. B. Susilo Nur Hakim, Fitro Nur Wakhidah Nurtriana Hidayati P Purwanto Pinem, Agusta Pranoto . Prind Triajeng Pungkasanti, Prind Triajeng Rahmat Gernowo Rastri Prathivi Rudi Hermawan Rudy Hartadi Rudy Hartadi Setiarso, Galih Tirta Yurista Kumkamdhani Titis Handayani Toni Wijanarko Adi Putra