Analisis Sentimen Kebijakan Penempatan Dana 200T Di Bank Bumn Menggunakan Algoritma Support Vector Machine

  • Taufik Ramlan Alfiansyah Universitas Bina Sarana Informatika, Indonesia
  • Audy Abdillah Hidayat Universitas Bina Sarana Informatika, Indonesia
  • Alfarezi Hidayat Pratama Universitas Bina Sarana Informatika, Indonesia
  • Agil Aqshol Mahenda Universitas Bina Sarana Informatika, Indonesia
  • Muhammad Rafly Universitas Bina Sarana Informatika, Indonesia
  • Fuad Nur Hasan * Mail Universitas Bina Sarana Informatika, Indonesia
DOI: https://doi.org/10.47065/comforch.v5i1.2329
Keywords: Sentiment Analysis; Public Policy; Support Vector Machine

Abstract

The policy of placing Rp200 trillion in state-owned banks (BUMN) has sparked extensive debate and elicited diverse public reactions. Frequently discussed issues include the transparency of the policy, potential risks to the national budget, and the role of the banking sector in strengthening liquidity and supporting economic recovery. Timely insights into public reception are essential so that government communication strategies and risk-mitigation measures can be better targeted. This study aims to map the direction of public sentiment, identify the most salient topics, and evaluate the extent to which computational classification approaches can be used to monitor opinions on an ongoing basis. The findings indicate clear polarization between support and criticism. Negative discussions typically emphasize accountability, governance, and concerns over fiscal risk, while positive discussions highlight the policy’s potential benefits for liquidity, smoother credit distribution, and overall economic stability. These results provide an empirical basis for government and industry stakeholders to sharpen key messages, clarify mechanisms and oversight processes, and anticipate issues that could lead to misinformation. In addition, sentiment monitoring can be conducted periodically as an early-warning system to detect shifts in public perceptions toward similar policies in the future.

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Published
2025-12-16
Issue
Vol 5 No 1 (2025): November 2025
Section
Articles

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