Asset Liability Management (ALM) can be overseen using financial ratios derived from financial statements. These statements provide a comprehensive picture of a company's status and necessitate analysis to evaluate performance. This research aims to analyze financial ratios to describe the financial condition, measure business development over time, and evaluate the achievement of the company's objectives. An optimization analysis of financial ratios is performed using the Weighted Goal Programming (WGP) model, which addresses multiple objectives by applying weights based on their priorities. The Best-Worst Method (BWM) was used to determine the priority weights of deviation variables from each financial ratio target. Financial ratios were selected based on their impact on profit using factor analysis. The constructed WGP model aims to minimize deviations in Return on Assets, Operating Ratios, Operating Income Ratio, Total Assets Turnover, and Current Ratio. Computational calculations to solve the WGP model are performed using Python, with pseudocode provided. A case study on a company in the garment and textile sector was conducted and found that the Operating Ratio, Return on Assets, Operating Income Ratio, and Current Ratio still need improvement by developing strategies to achieve the targets. Sensitivity analysis was also employed to assess the resilience of the model in response to alterations in data.

The purpose of this study is to analyze the factors influencing non-performing loans in companies listed on the Indonesian Stock Exchange Banking sector. All banks in Indonesia carefully review their Non-Performing Loans. According to the Central Bank regulations, the non-performing loan is at a maximum of 5%. Exceed the percentage; there will be one of the indications that the bank is experiencing difficulties and could potentially endanger business continuity. The researchers use the micro-economic and several macro-economic variables to predict the influencing factors toward the non-performing loan. Microeconomic variables studied are the ratio of bank capital to assets (CAP), the loans to deposits (LTD) ratio, the return to assets (ROA) ratio and the ratio of return to equity (ROE). Macroeconomic variables are the ratio of public sector debt to gross domestic product (DEBT), the surplus or deficit of the government budget to gross domestic product (FISCAL) ratio, the percentage increase in gross domestic product (GDP), annual inflation rate (INFL), and percentage of job seeker level (UNEMP). Researchers used some regression methods to analyze the results and the samples taken by researchers were companies listed in the banking sector during the period 2014-2017, and macroeconomic data in Indonesia during that year.