Preventive efforts to address online gambling behavior through islamic education learning with a deep learning approach for junior high school students
DOI:
https://doi.org/10.51468/jpi.v7i2.1082Keywords:
Online Gambling, Islamic Religious Education, Preventive Measures, Deep Learning, Middle School StudentsAbstract
The increasing involvement of students in online gambling activities has become a serious concern in the world of education, especially at the junior high school level. According to a 2024 report from the Indonesian Financial Transaction Reports and Analysis Center, approximately 960,000 students are involved in online gambling, which has a direct impact on declining academic achievement, psychological disorders, and moral degradation. Islamic Religious Education plays a strategic role in instilling religious values that can prevent deviant behavior such as online gambling. This study aims to: 1) analyze the application of the deep learning approach in Islamic Religious Education learning; and 2) identify preventive efforts carried out by teachers through Islamic Religious Education learning in tackling online gambling behavior. This study used a qualitative approach with a multi-site case study method in two Islamic boarding schools, namely Bhinneka Tunggal Ika Junior High School and Sunan Kalijogo Junior High School, which have implemented deep learning-based Islamic Religious Education learning. Data were obtained through classroom observations, in-depth interviews with teachers and students, and documentation studies. The results showed that the application of the deep learning approach through three principles: meaningful, mindful, and joyful learning has been proven to be effective in raising students' awareness of the dangers of online gambling. Furthermore, teachers play an active role in prevention through character building, discussions about religious values, and collaboration with parents and Islamic boarding school administrators. The results of this study are expected to contribute significantly to the development of learning models based on preventing deviant behavior in the digital age.
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