The study examines the impact of bullying on adolescent maturity in Bekasi, using methods of literary study. Factors such as the psychological condition of the perpetrators and victims, the family environment, and the school culture play a role in the occurrence of bullying. Bullying can lead to mental health disorders and decreased academic performance in adolescents, which in their behavior can hinder their progress towards maturity. The study analyzed patterns of relationships between bullying experiences and aspects of adolescent maturity, such as emotions, cognition, and behavior. Factors that moderate the negative impact of bullying are also being explored.

Research Objective: This study aims to determine the effect of  environmental costs and environmental performance on return on assets in energy companies listed in the Sharia Securities List.
Research Design/Methodology/Approach: The research method used quantitative descriptive analysis with secondary data, analysis tools are regression panel data.
Research Results:  The results show that simultaneously show that the variables of environmental costs and environmental performance together have a positive and significant effect on return on assets in energy companies listed in the Sharia Securities List. while partially showing that environmental cost variables have a negative and significant effect on return on assets in energy companies listed in the Sharia Securities List,  while environmental performance variables have a negative and insignificant effect on return on assets in energy companies listed in the Sharia Securities List.
Implications of Research Results: The implication of research results is that companies should do the need to increase environmental costs and environmental performance in an effort to increase sustainable company profitability.

In the business of selling goods, there must be goods that do not sell well and sell well. How to make unsold items sell well by giving customers a discount or discount strategy. The goal is to provide discounted prices to attract customers' attention and increase sales turnover. Prediction to give the right discount presentation is needed in the discount strategy. How to determine discount prediction using linear regression method, looking for line equations by training data taken from Kaggle.com. The data were trained to find the constants and coefficients of the independent variables. The resulting line equation will be tested to determine the discount prediction that will be given and calculate the error value. The data used is painting sales data taken from Kaggle.com, a total dataset of 1525, and a prediction calculation is made with 225 lines of test data. The input variable used is the price of the painting, and the output variable is the discount presentation. The process of evaluating the prediction results by calculating the MAE value, the difference between the actual data and the predicted data, the MAE value from the trial is 0.108.