Analysis of Global Bank’s Financial Performance with the Clustering K-Means Model - Santosa, Suhari; Heikal, Jerry (Magister Akuntansi Universitas Pancasila, 2024)
Purpose: The purpose of this study is to find out the financial performance of global banks in each cluster for the years 2019 and 2023. In addition, this study is also to find out the position of Indonesia's banks compared to global and ASEAN banks in 2019 and 2023. Methodology: The analysis model used is that the formation of clusters is based on the ratio of CAR, LDR, NIM, ROA and ROE. Testing was carried out with the K-Means model using SPSS. Findings: The results of the study show that in general, global banking performance in 2023 is better than in 2019 in 4 clusters out of 5 clusters. However, the number of banks in the Very Good and Good cluster has decreased in 2023 compared to 2019. In addition, the number of banks in the Very Bad cluster also increased in 2023 compared to 2019. Implication: The increase in the number of banks in the Very Bad cluster needs to be a concern, because the improvement in performance is not as good as other global banks. Local bank supervisory authorities, including the Financial Services Authority in Indonesia, need to pay attention to the performance of banks in the Very Poor cluster. Originality: This study provides additional information about the condition of banks compared to their peers in 2019 and 2023 at the global, ASEAN and Indonesia levels for bank management, investors and also authorities.