The study aims to estimate the effect of current ratio (CR), current liability to inventory (CLI), total asset turnover (TAT), net profit margin (NPM), sales growth (SG), and company size (FS) on profit growth (PG). The research population was 18 companies in the Food and Beverage (F&B) sector listed on the Indonesia Stock Exchange (IDX) from 2014-2018. The data estimation method uses the common effect panel data regression model. The empirical findings show that the CR and CLI ratios have a negative effect on PG, while the TAT, NPM, and SG ratios have a positive effect. Company size is a factor that does not affect the growth of company profits. The results of the study imply that an increase in company profits can be achieved if the company operates efficiently and with low liquidity to encourage higher sales growth. The limitations of the research are as follows: first, this research considers only one type of industry, hence the results of this study would not be the same if applied to another type of industry. Second, the author observes profit growth by using the company's financial ratios and size and ignores other factors that may affect profit growth, for example, the number of employees, total net sales, and market capitalization.

The purpose of this research is to develop an early warning system model that can anticipate the occurrence of delisting of Islamic stocks (ISSI) using Support Vector Machines (SVM). Financial variables used consist of debt to equity, return on invested capital, asset turn over, quick ratio, current ratio, return on assets, return on equity, leverage, long term debt, and interest coverage. The population of this study is 335 sharia shares registered at ISSI in the period 2012-2017, with a total sample of 102 companies. The results show that the financial variables had a predictive power to the occurrence of delisting of Islamic stocks in the ISSI index. The effect of the independent variable or predictor variable is the financial ratio to the target variable or the dependent variable that is the potential for delisting of Islamic stocks in the ISSI index. With the development of 4 SVM models with different levels of prediction accuracy, SVM Model 1 with an accuracy rate of 71.57%, SVM Model 2 with an accuracy rate of 72.55%, SVM Model 3 with an accuracy rate of 82.35% and SVM Model 4 with an accuracy rate of 100%, it can be concluded that the SVM Model 4 is the best model. .