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Pemanfaatan Ruang Masjid Suatu Kajian: Aktivitas Keagamaan Untuk Mengoptimalkan Peran dan Fungsi Masjid Muh Alfian Hayadi; Muh Nasrun; Muh Arqam Harbi; Sam'un Mukramin
CBJIS: Cross-Border Journal of Islamic Studies Vol. 5 No. 2 (2023): Desember
Publisher : Fakultas Tarbiyah dan Ilmu Keguruan, IAI Sultan Muhammad Syafiuddin

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.37567/cbjis.v5i2.2577

Abstract

Mosques are one of the important institutions in the Islamic religion and have a major role in the lives of Muslims. Apart from being a place of worship, explore the use of mosque space in religious activities. Observing the Nur Ichsan Mosque, District Land Office. Gowa, this research highlights the role of social, religious education, as well as the importance of the role and function of mosques in Muslim society. Field research with a qualitative approach, involving observations, interviews and case studies at the Nur Ichsan Mosque. Data analysis was carried out to understand the use of mosque space and the role of administrators in increasing religious activities. Highlighting the mosque space as the main center of worship, its social role, religious education, and the importance of mosque administrators in optimizing the function of the mosque. The paper review supports discussion of the central role of mosques in Islam and management strategies to maximize the role of mosques. Mosques have a central role in religious activities, religious education and social welfare. Through the case study of the Nur Ichsan Mosque, this conclusion supports the use of mosque space as a center for activities that are beneficial for Muslims and society. This journal discusses the importance of utilizing mosque space for religious activities as well as the role of effective management in maximizing the function of mosques in society.
Predictive Modeling of Suicide Ideation Risk of Bullying Victims Using Machine Learning Based on Questionnaire Data Andika Saputra; Mirnawati; Mispasari; Muh Nasrun; Muh. Arya Kusuma Wardana; Muhalis
Journal of Embedded Systems, Security and Intelligent Systems Vol 6, No 1 (2025): March 2025
Publisher : Program Studi Teknik Komputer

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.59562/nxxppw67

Abstract

Bullying is one of the main risk factors for mental health disorders in adolescents and is significantly correlated with increased suicidal ideation. This study aims to develop a predictive model of suicidal ideation risk in bullying victims using a questionnaire data-based machine learning approach as the basis for the development of an early warning system. The study used a predictive quantitative design involving 350 respondents who had experienced bullying. The variables analyzed included demographic factors, experiences of bullying, as well as psychological indicators such as depression, anxiety, stress, self-esteem, and social support. Four classification algorithms were compared, namely Logistic Regression, Random Forest, Support Vector Machine, and XGBoost. The results show that XGBoost has the best performance with an accuracy of 91% and a ROC-AUC of 0.94. The most influential variables on risk prediction were depression scores, social support, anxiety, and bullying frequency. These findings show that the machine learning approach is effective in supporting early detection of the risk of suicidal ideation and has the potential to be implemented as an early warning system in the educational environment.