Analisis Rasio Profitabilitas untuk Memprediksi Financial Distress menggunakan Metode Support Vector Machine

Abstract

Financial distress is when a company experiences difficulty fulfilling its obligations or struggles to pay off its obligations, which requires the company to take corrective action. This research aims to determine the accuracy of prediction models for coal sector companies listed on the Indonesia Stock Exchange for 2018-2022. This research analyzes company financial reports using secondary data collection techniques. The variables studied are the profitability ratio, which consists of Return on Assets, Gross Profit Margin, and Net Profit Margin. The object of this research is companies in the coal industry sub-sector. This prediction model predicts 18 company data from 32 samples tested, so prediction errors occur in 5 observation data samples. This model can predict companies, where 18 companies predicted not to experience financial distress and five companies predicted to experience financial distress due to the Return on Assets (ROA) and Net Profit Margin (NPM) values.