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All Journal Journal International of Lingua and Technology Journal International Dakwah and Communication Lingeduca: Journal of Language and Education Studies Pengabdian Jurnal Abdimas Sharia Oikonomia Law Journal International Journal of Language and Ubiquitous Learning Journal of World Future Medicine, Health and Nursing Darussalam: Journal of Psychology and Educational Journal of Computer Science Advancements Journal of Moeslim Research Technik Journal of Selvicoltura Asean Journal of Loomingulisus ja Innovatsioon Techno Agriculturae Studium of Research Research of Scientia Naturalis
Farah, Rina
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Religion Aerospace Engineering Agriculture, Biological Sciences & Forestry Humanities Automotive Engineering Chemistry Computer Science & IT Control & Systems Engineering Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Environmental Science Health Professions Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Medicine & Pharmacology Nursing Physics Public Health Social Sciences Veterinary Other

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Patent Law in Islamic Economics Challenges and Opportunities Marwal, Muhammad Ilyas; Amir, Syafiq; Farah, Rina
Sharia Oikonomia Law Journal Vol. 2 No. 3 (2024)
Publisher : Yayasan Pendidikan Islam Daarut Thufulah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/solj.v2i3.1409

Abstract

One important way to protect intellectual property rights is to use patent law to encourage creativity and innovation. In Islamic economics, the application of patent law raises several issues. This is because there are fundamental differences between the principles of Shari'a and some elements of conventional patent law. Since Islamic economics emphasizes justice, public interest, and equitable distribution of wealth, patent law must reflect these values. This study aims to identify and analyze the challenges and opportunities in the implementation of patent law in Islamic economics. Specifically, this study aims to understand the concepts and principles of patent law from an Islamic economic perspective, identify the main problems faced in the implementation of patent law in Muslim countries, explore opportunities for developing a patent legal framework that is in accordance with sharia principles, and provide. This research was conducted using qualitative methods, using literature studies and document analysis. Data were obtained from various sources, such as scientific journals, books, laws, fatwas, and other documents. The results of the study indicate that patent law in Islamic economics must balance individual rights and societal benefits. Some of the main problems identified include lack of knowledge about the importance of patents, inconsistencies between some aspects of conventional patent law and sharia principles, and resistance to changes in current regulations. According to this study, patent law in Islamic economics faces many challenges and opportunities. By incorporating sharia principles into the patent legal system, innovation and technological progress that benefit society can be increased.
The Role of Personality Test Results as a Tool for Student Self-Understanding and Its Implications in Counseling Zubaidah, Zubaidah; Nuramita, Nuramita; Nurfadila, Nurfadila; Asmawati, Asmawati; Zulfikar, Zulfikar; Farah, Rina
Darussalam: Journal of Psychology and Educational Vol. 4 No. 1 (2025)
Publisher : Yayasan Minang Darussalam

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70363/djpe.v4i1.253

Abstract

Self-understanding is one of the main keys for students to achieve academic success and personal development, especially during adolescence which is known as the phase of searching for identity. In the world of education, personality has an important role in shaping students' behavioral patterns, learning styles, and social interactions. One tool that can support students' self-understanding is a personality test. This article aims to discuss the role of personality test results as a means of students' self-understanding and its implications in guidance and counseling services at school.
The Future of Medical Technology: Recent Innovations in Artificial Intelligence and Robotics for More Precise and Efficient Treatment Farah, Rina; Nizam, Zain
Journal of World Future Medicine, Health and Nursing Vol. 3 No. 2 (2025)
Publisher : Yayasan Pendidikan Islam Daarut Thufulah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/health.v3i2.1896

Abstract

The rapid advancement of artificial intelligence (AI) and robotics has transformed the landscape of medical technology, offering unprecedented precision, efficiency, and personalization in patient care. The integration of AI-driven diagnostics and robotic-assisted surgery has improved clinical decision-making, minimized human errors, and enhanced surgical outcomes. This study aims to explore recent innovations in AI and robotics in the medical field, assess their effectiveness in improving treatment precision, and identify challenges in their widespread adoption. A systematic review methodology was employed, analyzing recent peer-reviewed articles, case studies, and reports from medical institutions and technology developers. The findings indicate that AI-powered diagnostic tools significantly enhance early disease detection, while robotic surgery enables minimally invasive procedures with improved accuracy and reduced recovery times. However, challenges such as ethical concerns, high implementation costs, and regulatory hurdles remain key barriers to full-scale adoption. This study concludes that AI and robotics will play an increasingly vital role in modern medicine, revolutionizing healthcare delivery. Further research should focus on optimizing AI algorithms, addressing ethical considerations, and developing cost-effective solutions to ensure broader accessibility and acceptance in medical practice.
The Utilization of Educational Technology to Improve the Bilingual Abilities of Elementary School Children: A Case Study of First and Second Language Interaction Dwanda Putra, Lovandri; Nur Rahmi, Sri; Farah, Rina
International Journal of Language and Ubiquitous Learning Vol. 3 No. 1 (2025)
Publisher : Yayasan Pendidikan Islam Daarut Thufulah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/ijlul.v3i1.2150

Abstract

Background. Educational technology is increasingly being used to support bilingual learning in elementary school children. The interaction between first and second languages in the context of education is still a challenge in formal learning. The use of technology is expected to be able to improve children's bilingual skills without reducing their first language competence. Purpose. This study aims to analyze the effectiveness of educational technology in improving the bilingual ability of elementary school children and understanding the interaction between first and second languages in the learning process. The study also explores the factors that contribute to the success of technology-based bilingual learning. Method. The research method uses a quantitative approach with a pseudo-experimental design. The sample consisted of elementary school students who were divided into control and experimental groups. The instruments used included language tests, observations, and interviews with teachers and parents. Data were analyzed using statistical tests to measure improvement in bilingual skills before and after technological interventions. Results. The results of the study show that the use of educational technology significantly improves children's bilingual skills. Second language scores increased higher than first languages, but without causing a decrease in first language competence. The factors of the duration of technology use, teacher guidance, and parental support play an important role in the effectiveness of technology-based bilingual learning. Conclusion. The conclusion of this study confirms that technology can be an effective tool in increasing bilingualism in elementary school children if used in a directed manner and supported by a conducive learning environment. The implications of this research provide new insights for the development of technology-based curriculum as well as the development of language learning applications that are more balanced in accommodating the first and second languages.
Comparing the Effectiveness of Two Approaches in Learning English in Indonesia Dewi, Nita Rosmala; Rahman, Rashid; Farah, Rina
Lingeduca: Journal of Language and Education Studies Vol. 4 No. 1 (2025)
Publisher : Yayasan Pedidikan Islam Daarut Thufulah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/lingeduca.v4i1.2185

Abstract

The teaching of English as a foreign language in Indonesia continues to face challenges, particularly in identifying the most effective instructional approach. Previous studies have shown varying results when comparing communicative and grammar-based methods in language acquisition. This study aims to compare the effectiveness of two dominant approaches: the Communicative Language Teaching (CLT) method and the Grammar-Translation Method (GTM) in improving English proficiency among secondary school students in Indonesia. Employing a quasi-experimental design, this research involved 120 students divided into two equal groups, each receiving instruction based on one of the approaches over a period of 12 weeks. Pre-tests and post-tests were administered to measure students’ progress in reading, writing, listening, and speaking skills. The results indicated that the CLT group significantly outperformed the GTM group, particularly in speaking and listening components, while the GTM group showed marginally better results in grammar and reading comprehension. The findings suggest that while both methods have merits, CLT offers a more balanced improvement in communicative competence. This study contributes to the ongoing discourse on English pedagogy in EFL contexts and provides evidence-based recommendations for curriculum development in Indonesian schools.
Building Bridges Between Languages with Generative AI: A Study on Zero-Shot Machine Translation and its Implications for Global Communication Yazidus, Muhammad; Farah, Rina; Huda, Nurul
Journal International of Lingua and Technology Vol. 4 No. 1 (2025)
Publisher : Sekolah Tinggi Agama Islam Al-Hikmah Pariangan Batusangkar, West Sumatra, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55849/jiltech.v4i1.825

Abstract

The increasing need for cross-lingual communication in a globalized world has driven innovations in machine translation, with the aim of breaking down language barriers. Traditional machine translation models rely on large parallel corpora for training, but zero-shot machine translation (MT) offers a promising alternative by enabling translation between language pairs without requiring direct training data. This study explores the potential of generative AI in zero-shot MT, focusing on its ability to bridge languages with minimal linguistic resources. The research aims to evaluate the effectiveness of zero-shot MT using generative AI models in translating between languages that lack extensive parallel corpora. The study uses a comparative approach, assessing the performance of generative AI models against traditional MT systems on several language pairs, particularly focusing on low-resource languages. The results show that generative AI-based zero-shot models can produce high-quality translations across multiple languages, even those with limited or no parallel data. The findings suggest that zero-shot MT has the potential to revolutionize global communication by offering a scalable, efficient solution for languages with insufficient resources. This research concludes that generative AI's ability to perform zero-shot machine translation has significant implications for improving cross-cultural communication and expanding access to information, with important applications in education, business, and diplomacy.
Empowering Communities through Digital Skills Training in Simeulue Village Jete, Rahmat; Farah, Rina
Pengabdian: Jurnal Abdimas Vol. 2 No. 4 (2024)
Publisher : Yayasan Pendidikan Islam Daarut Thufulah

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/abdimas.v2i4.2227

Abstract

Background. Social entrepreneurship has emerged as a strategic approach to address socio-economic disparities, especially in remote communities where access to economic opportunities and institutional support is limited. Purpose. This study aims to explore the development of social entrepreneurship in the remote region of Sidenreng Rappang, Indonesia, focusing on community-driven initiatives and their socio-economic impacts. Method. Employing a qualitative case study methodology, data were collected through in-depth interviews, participant observation, and document analysis involving local entrepreneurs, community leaders, and development agencies. Results. The findings reveal that successful social entrepreneurship in the region is driven by strong local leadership, the utilization of indigenous knowledge, and adaptive strategies that align with the community’s cultural and ecological context. Challenges identified include limited access to capital, insufficient training in entrepreneurial skills, and weak institutional support. Conclusion. The study concludes that fostering social entrepreneurship in remote areas requires a hybrid support system involving education, mentorship, policy facilitation, and community empowerment. This research contributes to the growing body of literature on inclusive development by highlighting the contextual dynamics of entrepreneurial ecosystems in marginalized areas
Public Speaking Strategy for Muslim Lecturers to Attract Generation Z in Da’wah Rintaningrum, Ratna; Razak, Faisal; Farah, Rina
Journal International Dakwah and Communication Vol. 5 No. 1 (2025)
Publisher : Sekolah Tinggi Agama Islam Al-Hikmah Pariangan Batusangkar, West Sumatra, Indonesia.

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.55849/jidc.v5i1.899

Abstract

The rise of Generation Z as a distinct demographic group has posed new challenges and opportunities for public speaking, especially in the field of da’wah (Islamic preaching). As digital natives, Generation Z engages with content in ways that differ significantly from previous generations, making it essential for Muslim lecturers to adapt their public speaking strategies to connect effectively with this audience. This research explores the public speaking strategies used by Muslim lecturers to attract and engage Generation Z in da’wah. The study employs a qualitative research design, conducting interviews with Muslim lecturers who have successfully used digital platforms and innovative methods to deliver their messages to younger audiences. The findings reveal that interactive content, visual aids, relevant social media usage, and humor are among the most effective strategies for engaging Generation Z. Lecturers who incorporated personal stories and interactive sessions found higher levels of engagement and greater impact. The study concludes that for Muslim lecturers to effectively attract Generation Z, they must embrace modern communication tools while maintaining the integrity and relevance of Islamic teachings. Future research should explore the long-term impact of these strategies and how they affect the retention of Islamic values among Generation Z.
Big Data Analysis to Predict Consumption Patterns in Smart Cities Susilo, Anto; Prasetiyo, Rachmat; Aslam, Bilal; Farah, Rina
Journal of Computer Science Advancements Vol. 3 No. 1 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/jsca.v3i1.1535

Abstract

The rapid development of smart cities has increased the demand for efficient resource management and personalized services, where understanding consumption patterns is crucial. Big data analysis offers a powerful tool for predicting these patterns, enabling city planners and service providers to make data-driven decisions to enhance urban living quality. This study aims to utilize big data analytics to predict consumption patterns across various sectors in smart cities, including energy, water, and transportation. By leveraging large datasets, this research seeks to provide actionable insights for optimizing resource allocation and anticipating future consumption demands. The methodology involves collecting and analyzing data from multiple sources, such as IoT sensors, public utility records, and social media, to identify consumption trends. Machine learning algorithms, including time series analysis and clustering, were applied to detect patterns and forecast demand. Results indicate that big data analytics can accurately predict consumption fluctuations, with an 85% accuracy in energy demand forecasting and a 78% accuracy in water usage prediction. The findings highlight correlations between demographic factors and consumption, providing a comprehensive understanding of urban needs. The study concludes that big data analysis is a valuable approach to managing resources effectively in smart cities. By predicting consumption patterns, city planners can proactively address demand surges, reduce waste, and improve resource distribution, ultimately supporting sustainable urban growth. Implementing these insights could significantly enhance smart city efficiency and resilience.
Machine Vision for Quality Control in Halal Food Production: A Deep Learning Approach A, Chevy Herli Sumerli; Farah, Rina; Nizam, Zain
Journal of Moeslim Research Technik Vol. 2 No. 3 (2025)
Publisher : Yayasan Adra Karima Hubbi

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.70177/technik.v2i3.2351

Abstract

Ensuring the quality and integrity of halal food products has become increasingly important with the growth of the global halal food industry. Conventional quality control methods, which rely on manual inspection and laboratory testing, are often time-consuming, subjective, and prone to human error. This study aims to develop and evaluate a machine vision system powered by deep learning algorithms to automate quality control processes in halal food production. A convolutional neural network (CNN)-based framework was implemented to classify and detect defects, contamination, and non-halal elements in food products. The system was trained using a dataset of 12,500 labeled images collected from halal-certified production facilities, with data augmentation applied to improve model generalization. Performance metrics, including accuracy, precision, recall, and F1-score, were used to evaluate the system. The results demonstrate that the proposed deep learning model achieved 96.8% classification accuracy, with high precision (95.5%) and recall (97.2%), significantly outperforming conventional machine vision techniques. The findings indicate that deep learning-driven machine vision can provide fast, reliable, and scalable quality control, supporting compliance with halal standards while reducing operational costs. This research highlights the potential of artificial intelligence to modernize quality assurance systems in halal food industries.  
Co-Authors A, Chevy Herli Sumerli Amir, Syafiq Anis, Nina Aslam, Bilal Asmawati Asmawati Dwanda Putra, Lovandri Fini Widya Fransiska, Fini Widya Harianta, Harianta Idris, Haziq Jete, Rahmat Manurung, Edison Hatoguan Marwal, Muhammad Ilyas Nampira, Ardi Azhar Nita Rosmala Dewi Nizam, Zain Nofirman, Nofirman NUR RAHMI, SRI Nuramita, Nuramita Nurfadila Nurfadila, Nurfadila Nurul Huda Prasetiyo, Rachmat Rahman, Rashid Ratna Rintaningrum, Ratna Razak, Faisal Sestri, Elliya Susilo, Anto Wardhani, Wahju Dyah Laksmi Yazidus, Muhammad Zubaidah R, Zubaidah Zulfikar Zulfikar