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All Journal JSI: Jurnal Sistem Informasi (E-Journal) Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) JURNAL TEKNIK INFORMATIKA DAN SISTEM INFORMASI Jurnal Teknoinfo Jurnal Nasional Komputasi dan Teknologi Informasi Journal of Information System, Applied, Management, Accounting and Research Jurnal Informatika Ekonomi Bisnis REMIK : Riset dan E-Jurnal Manajemen Informatika Komputer JOURNAL OF INFORMATION SYSTEM RESEARCH (JOSH) Jurnal Teknologi Informatika dan Komputer Journal of Computer Networks, Architecture and High Performance Computing Bulletin of Information Technology (BIT) Brilliance: Research of Artificial Intelligence Pelita Teknologi : Jurnal Ilmiah Informatika, Arsitektur dan Lingkungan SIGMA: Information Technology Journal Jurnal INKOFAR Jurnal Informatika Teknologi dan Sains (Jinteks) Jurnal Pengabdian Mandiri Malcom: Indonesian Journal of Machine Learning and Computer Science Jurnal Lentera Pengabdian Jurnal Informatika Ekonomi Bisnis Riwayat: Educational Journal of History and Humanities VIDHEAS: Jurnal Nasional Abdimas Multidisiplin RECORD Journal of Loyality and Community Development
Butsianto, Sufajar
Universitas Pelita Bangsa
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Journal : Jurnal Informatika Ekonomi Bisnis

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Analisis Sentimen Ulasan Aplikasi Jamsostek dengan SVM, Random Forest, dan Logistic Regression Butsianto, Sufajar; Rifa'i, Anggi Muhammad
Jurnal Informatika Ekonomi Bisnis Vol. 7, No. 3 (September 2025)
Publisher : SAFE-Network

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37034/infeb.v7i3.1266

Abstract

The digitalization of public services has encouraged the development of the Jamsostek Mobile (JMO) application by BPJS Ketenagakerjaan. This application is expected to provide convenience in accessing information, JHT claims, and other services. However, user reviews on the Google Play Store show diverse perceptions, ranging from satisfaction to technical complaints. This study aims to conduct sentiment analysis on user reviews of the JMO application by classifying opinions into positive, negative, and neutral sentiments. Data were collected through crawling from the Google Play Store and processed using text preprocessing stages, including data cleaning, case folding, stopword removal, tokenization, stemming, and Term Frequency–Inverse Document Frequency (TF-IDF) weighting. The classification process was then carried out using three machine learning algorithms, namely Support Vector Machine (SVM), Random Forest, and Logistic Regression. The results indicate that negative sentiment dominates with 46%, followed by positive sentiment at 40% and neutral at 14%. Most complaints are related to login difficulties, application errors, and technical bugs in claim features. In terms of algorithm performance, SVM with a linear kernel achieved the highest accuracy of 87.5% and an F1-score of 0.87, outperforming Random Forest (85.3%) and Logistic Regression (82.7%). Academically, this study reinforces the effectiveness of SVM in sentiment analysis using TF-IDF, while practically providing recommendations for BPJS Ketenagakerjaan to improve system stability, login speed, and reduce application bugs to enhance user satisfaction.
Co-Authors Abdul Halim Anshor Agung Nugroho Agus Suwarno Aguswin, Ahmad Ahmad Turmudi Zy Aldi Ramadhan Amali, Amali Ananto Tri Sasongko Andre Ardiansyah Andriani Andriani Andriani Andriani Anggi Muhammad Rifai Anisah Purnamasari Aprila Hardi, Resty Arief Nur Hidayat ARIF SUSILO Aris Iskianto Aris Iskianto2 Arwan Sulaeman, Asep Asep Muhidin Asep Muhidin Baharudin, Arya Rifaldi Budi Rahardjo, Sugeng Candra Naya Dewi Sekar Arum Dian Riki Pangestu Dicky Winanda Santoso Donny Maulana Edi Tri Triwibowo Edi Tri Wibowo Edora Edora Edy Widodo Edy Widodo Eka Nur Arifin Eko Putra, Fibi Elkin Rilvani Endah Yaodah Kodratillah Ermanto Ermanto Ermanto Fauzi Ahmad Muda febriyanti febriyanti Herdiyan, Serly Humam Fathurrahman Ikhsan Romli Irfan, Yusuf Kodratillah, Endah Yaodah Makmun Effendi, M. Mamat Casmat Maryani Manik Maulana, Futuh Muhamad Fatchan Muhammad Faisal Muhammad Fatchan Muhammad Fikri Fauzan muhidin, asep Muhtajuddin Danny Naya, Candra Nindi Tya Mayangwulan Nugroho, Agung Nurhali Saepudin Nurhali Saepudin Oktavianti, Risma Nadia Otib Subagja Pratama, Suria Puput Riyanti Purwanto Purwanto Putri Riandani, Andini Retno Fitri Astuti Retno Purwani Setyaningrum Rifa'i, Anggi Muhammad Romli S. Sunge, Aswan Selviana, Vina Setyawan, Wisnu Sifa Fauziah Sifa Fauziah, Sifa Siswandi , Arif Siswandi, Arif Siti Rahayu Sulaeman, Asep Arwan Sunge , Aswan S. Supriyanto, Asep Suratman Suratman Syahlan Sugiarto Tedi, Nanang Triwibowo, Edi Turmud Zy, Ahmad Valentin*, M Ryan Bagus Wachid Hasyim, Wachid Widiyatmoko, Arif Tri Wiyanto Wiyanto Wiyanto Yolanda Alviana