Penerapan Algoritma Naive Bayes untuk Prediksi Financial Distress pada Perusahaan Publik sebagai Upaya Digitalisasi Analisis Akuntansi

Authors

  • Nur Shafwa Aulia Sitorus Universitas Islam Negeri Sumatera Utara
  • Muhammad Fathir Aulia Universitas Islam Negeri Sumatera Utara
  • Nayla Faiza Universitas Islam Negeri Sumatera Utara
  • Hervilla Amanda R. Siregar Universitas Islam Negeri Sumatera Utara

DOI:

https://doi.org/10.26418/jaakfe.v14i2.101099

Abstract

Perkembangan teknologi digital mendorong penerapan kecerdasan buatan dalam bidang akuntansi untuk meningkatkan akurasi dan efisiensi analisis keuangan. Penelitian ini bertujuan menerapkan algoritma Naive Bayes guna memprediksi kondisi financial distress pada perusahaan publik sektor manufaktur di Indonesia sebagai bagian dari digitalisasi analisis akuntansi. Data yang digunakan berupa 150 entri rasio keuangan, meliputi Current Ratio (CR), Return on Assets (ROA), Net Profit Margin (NPM), dan Total Asset Turnover (TATO). Model dievaluasi menggunakan metrik akurasi, precision, recall, dan F1-score. Hasil penelitian menunjukkan akurasi sebesar 86,67%, precision 75%, recall 25%, dan F1-score 37,5%. Temuan ini menunjukkan bahwa Naive Bayes cukup efektif dalam mengklasifikasi perusahaan Non-Distress, namun masih perlu pengembangan untuk meningkatkan deteksi kelas Distress. Model ini berpotensi menjadi dasar pengembangan sistem deteksi dini berbasis digital dalam analisis keuangan perusahaan.

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Published

2026-02-19