Prediksi Potensi Kebangkrutan PT Argo Pantes Tbk Periode Tahun 2014-2024 (Implementasi Model Zmijewski X-Score) - Masayu Adisya Auradinda Pratiwi; Divianto Divianto; Yulia Pebrianti (Jurnal Riset dan Inovasi Manajemen, 2025)
This study aims to predict the potential bankruptcy of PT Argo Pantes Tbk for the period 2014–2024 using the Zmijewski X-Score model. The research adopts a quantitative method based on secondary data obtained from the company’s published annual financial statements. The Zmijewski model was selected because of its effectiveness in assessing companies with unstable financial conditions and its ability to provide a more accurate reflection of financial distress compared to other models. The analysis process involved calculating the X-Score for each year within the observation period and interpreting the results according to the criteria of the model. The findings indicate that for the entire study period, the calculated X value was consistently greater than or equal to zero. This outcome signifies that the company is in a condition classified as potentially bankrupt. Furthermore, the model demonstrated 100% accuracy in describing the company’s actual financial situation, since PT Argo Pantes Tbk consistently recorded net losses throughout the period of analysis. These losses were not incidental but reflected a long-term pattern of weak financial performance, limited profitability, and declining competitiveness in the textile industry. The results highlight that PT Argo Pantes Tbk has been operating under severe financial distress for a prolonged period, with no indication of recovery during the years observed. The persistent losses and negative financial indicators reinforce the conclusion that the company is in an unhealthy condition. The study confirms the applicability and reliability of the Zmijewski X-Score as a bankruptcy prediction tool in the Indonesian context, particularly for firms experiencing prolonged instability. Overall, the study provides valuable insights into financial distress analysis and underscores the importance of early bankruptcy prediction models in supporting stakeholders, investors, and regulators in making informed decisions.