Jurnal Indonesia Sosial Teknologi

Students' Perception of the Use of Arabic Language Learning Applications (Al-Kunuz and Rosetta Stone) in Online Learning in Islamic Universities

Mubarok Fatahillah — 2025-12-02

This research aims to evaluate students' perceptions of the use of Arabic language learning applications, Al-Kunuz and Rosetta Stone, in the context of online learning in Islamic universities, especially at STAI Kuningan. The method used is a quantitative approach with a descriptive research design, involving 100 students as respondents. Data were collected through questionnaires measuring students' perceptions of the ease of use and effectiveness of the applications in improving speaking, listening, reading, and writing skills. The results showed that the Al-Kunuz app received positive ratings for improving speaking and listening skills, with average scores of 4.2 and 4.3, respectively, while the Rosetta Stone app was more effective in improving reading and writing skills, with average scores of 4.2 and 4.1. Linear regression analysis revealed a significant relationship between the use of the two apps and the improvement of students' Arabic language skills, with an R-squared value of 0.76. This indicates that 76% of the variation in Arabic language skills improvement can be explained by the use of the apps. However, several obstacles—such as unstable internet connections and the need for training in application use—hinder optimizing the use of this technology. These findings provide important insights for the development of technology-based Arabic language learning in Islamic universities, with particular attention to improving infrastructure and training for both teachers and students.

The Role of Technology in Arabic Language Learning: Innovation and Challenges in the Digital Age

Mubarok Fatahillah — 2025-12-02

This research aims to measure the effect of technology use in Arabic language learning on improving students' language skills at STAI Kuningan. Using a quantitative approach with a simple linear regression analysis method, this study involved 100 respondents consisting of students and teachers. Data were obtained through questionnaires distributed to respondents and analyzed to identify the relationship between technology use and Arabic language skills. The results of the study showed a significant positive relationship between the two variables. Every additional hour of technology use per week increased Arabic language skill scores by 3.679 points. The linear regression analysis showed an R Square value of 0.988, indicating that 98.8% of the variation in Arabic language skills can be explained by technology use. The validity and reliability tests of the research instrument also showed good results, with a Cronbach's Alpha value of more than 0.7. This study recommends that STAI Kuningan strengthen the use of technology in Arabic language learning to improve students' skills more effectively and efficiently.

Optimizing Early Detection of Early Childhood Developmental Disorders: The Role of Artificial Intelligence (AI) and Parental Involvement in Effective Interventions

Husnul Hafidhoh — 2025-12-02

Early detection of developmental anomalies in children is crucial for timely intervention, which can significantly enhance long-term developmental outcomes. This study aims to evaluate the effectiveness of an artificial intelligence (AI)-based detection tool and parental involvement in identifying and managing developmental disorders in children aged 2 to 6 years. A longitudinal research design was employed, involving 300 children exhibiting early signs of developmental disorders and 150 children in a control group. Data were collected through behavioral observation, AI-based analysis of video and audio interactions, and interviews with parents and educators. The findings revealed that the AI tool demonstrated high sensitivity in detecting motor, language, and autism-related disorders. Children who received early interventions showed significant improvements, particularly in motor skills, language development, and social interaction. Parental involvement in the intervention process further accelerated these improvements. This study highlights the potential of AI to enhance early detection and intervention, especially in resource-limited areas, and underscores the importance of engaging parents in the developmental process of their children. These findings contribute to the understanding of how AI can be integrated into early childhood care programs to improve outcomes for children with developmental challenges.