This study aims to explore the impact of the Covid-19 pandemic on the literacy levels of Indonesian students, with a focus on changes in reading habits and the application of literacy in daily life. The methodology used in this research is a descriptive approach combining both quantitative and qualitative methods. Data were collected through questionnaires and interviews, which were analyzed to measure students' literacy interest levels and to understand their views on literacy. The results show that the pandemic has led to a significant decline in students' reading habits, caused by factors such as online learning, digital fatigue, limited access to reading materials, and increased use of social media. To address this, it is recommended to provide broader access to reading materials and create an environment that supports literacy, both at school and at home.

Python programming language is a popular programming language in the field of data analysis. In this research, researchers will analyze data on the cause of lung cancer, because lung cancer has the highest death case among other cancer types. The purpose of the research is to explore how dataset processing related to lung cancer-causing factors using the Python programming language and the datasets used are derived from Kaggle. The research method used is quantitative with a population of 462,000 people and a sample of 999 people. The analysis technique used is an explorative data analysis technique. From the results of the research, the highest cause of lung cancer was found in people aged 32-42 years, level 7 genetic factor, 7th level in dust allergies, level 7 obesity and male sex has higher risk than women.
 

Music has become an important part of mental healing efforta. This is because music can reduce anxiety, such as symptoms of depression, anxiety, fear and have a positive effect on mood. However, research that describes statistically and explains visually is still rarely done. Therefore, this study aims to describe statistically and visualize the effectiveness of music as a healing of mental disorders. Through the literature study method, namely the search for references related to mental diseases and music, and pyton analysis, namely to conduct statistical data analysis and visualize data. The results explained that sufferers of mental disorders who listen to music are anxiety, depression, insomnia, OCD, the average age of listening to music that is affected by mental disorders of 14 years to 20 years as many as 300 people, on average per day listening to music for three hours a day as many as 175 as many as 175 People, the effectiveness of healing listening to music as many as 548 people from 736 people or in a percentage of 74.5% of the success rate of music in curing mental illness. This study proves that mental disorders can be cured by listening to music, especially music with rock and pop genres. This research contributes to the knowledge of listening to music into an alternative to healing mental disorders.Therefore future research is necessary to study in other mental disease disorders, not limited to patients with anxiety, Isomania, depression, OCD.