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All Journal EL-MUHASABA Jurnal Acitya Ardana: Jurnal Keuangan Negara dan Kebijakan Publik
Aldy Hermansyah
Politeknik Keuangan Negara STAN
Economics, Econometrics & Finance Education Environmental Science Social Sciences Other

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Analisis Konseptual Tax Sentiment Intelligence untuk Meningkatkan Kepatuhan Pajak di Indonesia Aldy Hermansyah; Roni Nur Hidayat; Ilham Ma'ruf Priyanto
EL MUHASABA: Jurnal Akuntansi (e-Journal) Vol 17, No 2 (2026): EL MUHASABA
Publisher : Jurusan Akuntansi Fakultas Ekonomi Universitas Islam Negeri Maulana Malik Ibrahim Malang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.18860/em.v17i2.37670

Abstract

Purpose: This study conceptually examines the application of Tax Sentiment Intelligence based on artificial intelligence as an innovation to improve tax compliance in Indonesia while exploring the relationship between trust in tax authorities, public perception in digital spaces, and taxpayer compliance. Method: A systematic literature review for the period 2020–2025 was conducted using Google Scholar, OpenAlex, and CrossRef via Publish or Perish, and article selection followed the PRISMA protocol, resulting in 11 relevant studies. Results: The bibliographic analysis identified two main clusters with weak interconnections: the methodological cluster of sentiment analysis techniques and the applied cluster of technology in public administration and taxation, with the framework and system nodes serving as connectors that underscore the urgency of an integrative framework. The literature synthesis indicates that negative public sentiment on social media correlates with weakened tax morale and declining voluntary compliance, while positive perceptions of tax authorities significantly promote compliance. Trust in tax institutions acts as the primary mediator between public perception and compliance behavior, but it can be undermined by perceptions of corruption or negative narratives circulating in the digital space. The integration of AI and NLP enables real-time sentiment monitoring, detection of shifts in collective sentiment, and early warning functions for the Directorate General of Taxes Implications: The study recommends developing a Tax Sentiment Dashboard that combines diverse data sources, validation and cleansing mechanisms, locally adaptive algorithms, and interpretation modules that link sentiment indices with compliance indicators. Novelty: This research proposes an initial conceptual framework for applying AI-based sentiment analysis in the Indonesian taxation context.
Analisis Sentimen Publik terhadap Pembentukan Danantara dengan Pendekatan VADER: Sebuah Studi Berbasis Media Sosial X Fadilatul Hilmiyah; Dina Damalia; Aldy Hermansyah
Jurnal Acitya Ardana Vol 5 No 2 (2025): Desember 2025 (INPRESS)
Publisher : Politeknik Keuangan Negara STAN

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Penelitian ini bertujuan untuk menganalisis dan memahami sentimen publik terhadap kebijakan pembentukan Danantara. Metode penelitian yang digunakan adalah Lexicon Based dengan pendekatan VADER untuk melakukan analisis dan klasifikasi sentimen publik. Dengan menggunakan data tweet dari media sosial X dan melalui tahapan crawling data, preprocessing, Labelling data, dan visualization, penelitian ini menganalisis 420 data tweet. Hasil penelitian menunjukkan dominasi sentimen positif sebesar 53% yang mencerminkan optimisme publik terhadap potensi Danantara, tetapi juga dipengaruhi oleh tweet bersifat netral dari akun berita dan akun resmi pemerintah, serta 47% sentimen negatif didasarkan atas kekhawatiran masyarakat khususnya dalam transparansi tata kelola dan kebermanfaatan Danantara untuk masyarakat. Hasil analisis didukung visualisasi word cloud yang menunjukkan dominasi kata "investor," "uang," "penting," "aksi," dan "BUMN" pada sentimen positif, serta kata "korupsi,", "ekonomi”, “transparan”, dan "kelola" pada sentimen negatif.
Co-Authors Dina Damalia Fadilatul Hilmiyah Ilham Ma'ruf Priyanto Roni Nur Hidayat