Evaluasi Komunikasi Publik dan Kualitas E-Government: Analisis Sentimen Ulasan Aplikasi Bapenda Sulsel Mobile di Google Play Store

  • Nurdyansa Nurdyansa Program Studi Ilmu Komunikasi, Fakultas Ilmu Sosial dan Ilmu Politik, Universitas Pancasakti Makassar
  • Ilhamsyah Azikin Program Studi Ilmu Pemerintahan, Fakultas Ilmu Sosial dan Ilmu Politik, Universitas Pancasakti Makassar
  • Fatma Fatma Program Studi Ilmu Pemerintahan, Fakultas Ilmu Sosial dan Ilmu Politik, Universitas Pancasakti Makassar
Keywords: analisis sentimen, e-government, kualitas layanan, komunikasi publik, Bapenda Sulsel Mobile

Abstract

Transformasi digital pelayanan pajak daerah menghadirkan kanal umpan balik publik yang organik dan berkelanjutan melalui platform distribusi aplikasi. Penelitian ini mengevaluasi kualitas e-government dan efektivitas komunikasi publik aplikasi Bapenda Sulsel Mobile dengan menganalisis 640 ulasan pengguna di Google Play Store (Juni 2022–April 2026). Menggunakan analisis sentimen berbasis pembelajaran mesin (TF-IDF + Logistic Regression, akurasi 88,0%, AUC 92,9%) yang dipadukan dengan pemetaan aspek terhadap kerangka kualitas layanan e-government, studi ini menemukan: (1) distribusi sentimen 68,8% positif dan 23,9% negatif; (2) kesenjangan kualitas berupa efisiensi yang diakui tinggi (57 dari 69 sebutan positif) dan reliabilitas yang lebih banyak dikeluhkan (66 dari 95 sebutan negatif); (3) dua insiden teknis episodik (Januari 2023 dan Juni 2024) yang memuncak pada kenaikan sentimen negatif; serta (4) peningkatan responsivitas institusional (tingkat balasan dari 4,4% pada 2023 menjadi 36,9% pada 2025). Secara kualitatif, ketidakpercayaan publik terkonsentrasi pada isu pungutan liar di Samsat, inkonsistensi tarif, dan kegagalan rekonsiliasi pembayaran. Studi ini menempatkan ulasan app-store sebagai instrumen evaluasi layanan publik digital yang melengkapi survei konvensional.

References

Afiyah, S. (2024). The Impact of E-Government Services, Citizen Participation, and Transparency on Public Trust in Government. Global International Journal of Innovative Research, 2(6), 1246-1261. https://doi.org/10.59613/global.v2i6.200

A'la, F. Y. (2022). Indonesian Sentiment Analysis towards MyPertamina Application Reviews by Utilizing Machine Learning Algorithms. Journal of Informatics Information System Software Engineering and Applications (INISTA), 5(1), 80-91. https://doi.org/10.20895/inista.v5i1.838

Alfarizi, M. I., Syafaah, L., Lestandy, M. (2022). Emotional Text Classification Using TF-IDF (Term Frequency-Inverse Document Frequency) And LSTM (Long Short-Term Memory). JUITA : Jurnal Informatika, 10(2), 225. https://doi.org/10.30595/juita.v10i2.13262

Al-Kautsar Maktub, M., Handayani, P. W., Sunarso, F. P. (2025). Citizen acceptance and use of the Jakarta Kini (JAKI) e-government: Extended unified model for electronic government adoption. Heliyon, 11(2), e42078. https://doi.org/10.1016/j.heliyon.2025.e42078

Alshuraiqi, H. S. (2020). Improved Term Frequency Inverse Document Frequency (TF-IDF) Method for Arabic Text Classification. International Journal of Advanced Trends in Computer Science and Engineering, 9(5), 6939-6946. https://doi.org/10.30534/ijatcse/2020/11952020

Asri, Y., Kuswardani, D., Suliyanti, W. N., Manullang, Y. O., Ansyari, A. R. (2025). Sentiment analysis based on Indonesian language lexicon and IndoBERT on user reviews PLN mobile application. Indonesian Journal of Electrical Engineering and Computer Science, 38(1), 677. https://doi.org/10.11591/ijeecs.v38.i1.pp677-688

Azzahra, W. L., Jamaludin Indra, Rahmat, R., Sutan Faisal (2025). Sentiment Analysis of User Reviews of the AdaKami Online Loan App from the App Store Using SVM and Naive Bayes. Journal of Applied Informatics and Computing, 9(3), 838-850. https://doi.org/10.30871/jaic.v9i3.9536

Broomfield, H., Reutter, L. (2022). In search of the citizen in the datafication of public administration. Big Data & Society, 9(1). https://doi.org/10.1177/20539517221089302

Choi, H., Cucciniello, M. (2026). Citizen‐Centered Public Service Design in Agile Digital Transformation: Insights From Public Mobility Services. Public Administration. https://doi.org/10.1111/padm.70059

Dahlström, C., Nistotskaya, M., Tyrberg, M. (2018). Outsourcing, bureaucratic personnel quality and citizen satisfaction with public services. Public Administration, 96(1), 218-233. https://doi.org/10.1111/padm.12387

Handayani, T., Mardiyati, S. (2026). Machine Learning-Based Sentiment Classification of Reviews from Indonesian Mobile Applications Using TF-IDF. Journal Mobile Technologies (JMS), 4(2), 95-105. https://doi.org/10.59431/jms.v4i2.972

Helmiyah, S., Pramestiawan, R. (2025). Analisis Komparatif Algoritma Machine Learning dengan Metrik Akurasi, Presisi, Recall, dan F1-Score pada Dataset Kacang Kering. Jurnal Ilmu Komputer dan Teknologi, 6(3), 152-159. https://doi.org/10.35960/ikomti.v6i3.2031

Jazuli, A., Widowati, Kusumaningrum, R. (2023). Aspect-based sentiment analysis on student reviews using the Indo-Bert base model. E3S Web of Conferences, 448, 02004. https://doi.org/10.1051/e3sconf/202344802004

Kent, M. L., Lane, A. (2021). Two-way communication, symmetry, negative spaces, and dialogue. Public Relations Review, 47(2), 102014. https://doi.org/10.1016/j.pubrev.2021.102014

Long, Y., Yang, K., Huang, R., Yuan, G., Xia, Y. (2026). Enhancing citizen satisfaction with mobile government services in China: The mediating role of trust in service quality and perceived value. Telematics and Informatics, 104, 102355. https://doi.org/10.1016/j.tele.2025.102355

Nashiroh Ramadhani, M., Ditha Tania, K., Afrina, M. (2026). Knowledge Discovery in Sharia Mobile Banking Reviews Using Aspect-Based Sentiment Analysis and Machine Learning. Journal of Applied Informatics and Computing, 10(1), 640-650. https://doi.org/10.30871/jaic.v10i1.11753

Nevrada, N. A., Syaputra, M. A. (2025). Sentiment Analysis of Telegram App Reviews on Google Play Store Using the Support Vector Machine (SVM) Algorithm. Journal of Applied Informatics and Computing, 9(1), 96-105. https://doi.org/10.30871/jaic.v9i1.8851

Nie, L., Wang, H. (2023). Government responsiveness and citizen satisfaction: Evidence from environmental governance. Governance, 36(4), 1125-1146. https://doi.org/10.1111/gove.12723

Rahayu, S. P., Afuan, L., Yunindar, G. A. (2025). Implementation of Text Mining on Song Lyrics for Song Classification Based on Emotion Using Website-Based Logistic Regression. Jurnal Teknik Informatika (Jutif), 6(1), 359-368. https://doi.org/10.52436/1.jutif.2025.6.1.4429

Sadiq, S., Umer, M., Ullah, S., Mirjalili, S., Rupapara, V., Nappi, M. (2021). Discrepancy detection between actual user reviews and numeric ratings of Google App store using deep learning. Expert Systems with Applications, 181, 115111. https://doi.org/10.1016/j.eswa.2021.115111

Sarvestani, M. (2025). An NLP-Based Framework for Sentiment and Topic Analysis of Citizen Feedback on U.K. Government Mobile Applications. IEEE Access, 13, 210360-210377. https://doi.org/10.1109/access.2025.3641669

Shen, C., Xu, Y., Yuan, Z. (2025). Digital dialogue in smart cities: Evidence from public concerns, government responsiveness, and citizen satisfaction in China. Cities, 158, 105717. https://doi.org/10.1016/j.cities.2025.105717

Sijabat, R. (2020). Analysis of e-Government Services: A Study of the Adoption of Electronic Tax Filing in Indonesia. Jurnal Ilmu Sosial dan Ilmu Politik, 23(3), 179. https://doi.org/10.22146/jsp.52770

Sofiani, S. (2023). ANALYSIS OF THE INFLUENCE OF SYSTEM QUALITY, INFORMATION QUALITY AND SERVICE QUALITY ON ANCOL APP USER SATISFACTION. International Journal Of Tourism, 2(1). https://doi.org/10.47256/ijt.v2i1.190

Suhendro, F. H., Rochman, D. D. (2025). M-Health Service Quality Analysis of Kimia Farma Mobile Application on Google Play Store Using Sentiment Analysis and Topic Modeling Methods. Dinasti International Journal of Economics, Finance & Accounting, 6(5), 3817-3827. https://doi.org/10.38035/dijefa.v6i5.5176

Thi Thu Hang, N. (2026). Public Policy Communication in the Digital Era: Building Trust, Transparency, And Citizen Engagement. International Journal of Social Science and Human Research, 09(07). https://doi.org/10.47191/ijsshr/v9-i7-24

Published
2026-06-10
How to Cite
Nurdyansa, N., Azikin, I., & Fatma, F. (2026). Evaluasi Komunikasi Publik dan Kualitas E-Government: Analisis Sentimen Ulasan Aplikasi Bapenda Sulsel Mobile di Google Play Store. ORE: ournal of ommunication esearch, 4(2), 1-19. etrieved from https://journal.unpacti.ac.id/index.php/CORE/article/view/2918
Abstract viewed = 56 times
PDF downloaded = 28 times